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Instituto Tecnológico y de Estudios Superiores de Monterrey
Campus Monterrey
School of Engineering and Sciences
“Road Load Data Acquisition system with SAE-J1939 Communications
Network: Integration and Laboratory Test”
A thesis presented by
Oscar Orellana Cruz
Submitted to the
School of Engineering and Sciences
in partial fulfillment of the requirements for the degree of
Master of Science
In Manufacturing Systems
Monterrey Nuevo León, May 14th, 2018
2
Instituto Tecnológico y de Estudios Superiores de Monterrey Campus Monterrey
School of Engineering and Sciences
The committee members, hereby, certify that have read the thesis presented by Oscar
Stalin Orellana Cruz and that it is fully adequate in scope and quality as a partial requirement
for the degree of Master of Science in Manufacturing Systems
_______________________
Dr. Ruben Morales Menendez
Associate Dean of Graduate Studies
School of Engineering and Sciences
_______________________
Dr. Ciro Rodríguez González
Tecnológico de Monterrey
School of Engineering and
Sciences
Principal advisor
_______________________
Dr. Héctor Siller Carrillo
University of North Texas
Department of Engineering
Technology
Co-advisor
_______________________
Dr. Oscar Martínez Romero
Tecnológico de Monterrey
School of Engineering and
Sciences
Committee member
_______________________
Dr. Federico Guedea Elizalde
Tecnológico de Monterrey
School of Engineering and
Sciences
Committee member
3
Monterrey Nuevo León, May 14th, 2018
Declaration of Authorship
I, Oscar Stalin Orellana Cruz declares that this thesis titled, “Road Load Data
Acquisition system on Heavy Trucks with SAE-J1939 Communications Network:
Integration and Experiments” and the work presented in it is of my own. I confirm that:
This work was done wholly or mainly while in candidature for a research degree at
this University.
Where any part of this thesis has previously been submitted for a degree or any other
qualification at this University or any other institution, this has been clearly stated.
Where I have consulted the published work of others, this is always clearly attributed.
Where I have quoted from the work of others, the source is always given. With the
exception of such quotations, this thesis is entirely of my own work.
I have acknowledged all main sources of help.
Where the thesis is based on work done by myself jointly with others, I have made
clear exactly what was done by others and what I have contributed by myself.
___________________________
Oscar Stalin Orellana Cruz
Monterrey Nuevo León, May 14th, 2018
©2018 by Oscar Orellana Cruz
All rights reserved
4
Dedication
This thesis is special dedicated to my mother, to whom I have always tried to give the best
of myself and who I have always had support in all the projects of my life, to my father
who has always been an example of perseverance and mettle, but at the same time, to
whom I have tried to show that there are different ways to achieve success and to my
brothers to whom, as a role model, I try to show that, although there is a long way to go to
reach our goals, it depends on the opportunities that you generate and the conviction that
you have.
I also want to give a dedication to close people who with their example have managed to
break schemes and get ahead, as are my uncle Juan Cruz, my cousin Byron Rojas and my
best friend Luis Angel Cruz.
Finally, a special dedication to those family members who are no longer with us, especially
my great aunt Maria Jaramillo, who strengthened in me family unity and humility values
enough to find happiness.
To God.
5
Acknowledgements
I want to thank all those who supported and motivated the idea of growing
professionally, especially one of my best friends, Ana María Salas, and Hans Witte, who was
my boss at Tecnova Ecuador who indirectly managed to encourage my search for a master
without thinking that their support would become for me an opportunity to demonstrate my
capability in this prestigious institution. Thanks to all the colleagues and friends who were
able to form during this time, friends whom I consider family and who were always present
to share experiences and knowledge.
I want to thank the confidence and opportunity given by Dr. Hector Rafael Siller
Carrillo, who was director of this master's program, and Dr. Ciro Angel Rodríguez González,
current principal advisor for supporting the initiatives and providing the necessary resources
to complete the project. I also want to thank MSc. Pedro Antonio Orta Casatañon and Dr.
Christian Carlos Mendoza Buenrostro for the academic support they could provide
throughout the project.
I would like to give special recognition to the Navistar company Navistar and its
support staff for the project, especially to the Engr. Laura Piña who shared her knowledge
and experience to boost the understanding of the project.
Finally, I would like to thank CONACYT and the Tecnológico de Monterrey for the
financial support, the opportunity to belong to a research group and for the motivation to
study and obtain the Master's degree.
6
“Road Load Data Acquisition system with SAE-J1939
Communications Network: Integration and Laboratory Test”
By
Oscar Orellana Cruz
Abstract
This thesis discloses the results of a reliability analysis (R&R Study) through
comparative method to validate a data acquisition (DAQ) system developed and built as a
prototype. The laboratory conditions were established in order to test and validate the
prototype when it acquires signals from accelerometers and strain gages as well as parameters
taken from the electronic control unit (ECU), in this case a truck.
The prototype equipment is composed of 9030 Compact RIO system with NI 9862
module for Controller Area Network (CAN) SAE J1939 and NI 9206 for analog inputs. 800
Hz sampling rate is programmed with LabVIEW code to acquire, store and analyze
information.
For the truck parameters, the code developed by Armando Ramírez in his research
[6] was replicated and integrated into the code developed for the acquisition of signals with
a user-friendly and versatile interface. The parameters are accelerator pedal position, engine
speed, engine coolant temperature and wheel-based vehicle speed, with these parameters is
possible to analyze the driving mode during the road tests.
Instrumentation for acceleration was developed on a shaker to acquire the data, the
frequency and wave amplitude were controlled by the use of a signal generator and signal
amplifier. The reference data is acquired by a Brüel & Kjaer (B&K) module model 3160-A
pattern equipment with PULSE Time Data Recorder software.
7
Instrumentation for strain measurements was developed by simulating the strain gage
measurement using a variable precision resistor. The reference data is acquired by a B & K
module model 3160-A pattern equipment with PULSE Time Data Recorder software and two
multimeters: OTC 55 series and MUL-280. The analysis range for these measurements is 0
to 80 Hz.
The selected equipment demonstrated the DAQ system capability to perform
vibration and deformation measurements with a resolution of 0.1 g and 100 μɛ respectively
in the frequency range from 0 to 80 Hz, as well as obtain parameters from CAN J1939
protocol at the same time.
8
Contents
List of Tables ......................................................................................................... 11
List of Figures ........................................................................................................ 11
Chapter 1 ............................................................................................................... 13
1 Introduction .................................................................................................... 13
1.1 Motivation .................................................................................................................. 14
1.2 Problem Statement .................................................................................................... 14
1.3 Thesis Hypothesis ...................................................................................................... 15
1.4 Objective ..................................................................................................................... 15
1.4.1 Specific Objectives ............................................................................................... 16
1.5 Thesis Content ........................................................................................................... 16
1.6 Thesis Scope ............................................................................................................... 17
Chapter 2 ............................................................................................................... 18
2 Literature Review ............................................................................................. 18
2.1 State of Art ........................................................................................................... 18
2.1.1 DAQ System ......................................................................................................... 19
2.1.2 CAN BUS Data Collection System ..................................................................... 21
2.2 Standards .............................................................................................................. 23
2.2.1 Tolerance of Vibration Measurement System .................................................. 23
2.2.2 Vibration calibration by comparison to a reference transducer ..................... 24
2.3 Summary .................................................................................................................... 25
Chapter 3 ............................................................................................................... 27
3 System Implementation ..................................................................................... 27
3.1 Introduction .......................................................................................................... 27
3.2 Objectives ............................................................................................................. 28
3.3 Methods and Materials ........................................................................................ 28
3.3.1 Hardware and Software Configuration ............................................................. 28
3.3.2 Software application for Electrical Validation ................................................. 30
3.3.3 Test Setup – Electrical Evaluation ..................................................................... 31
3.3.4 Analysis of Electrical Validation Tests .............................................................. 33
3.3.5 Software application for CAN J1939 data ........................................................ 34
3.3.6 Data Collection Integration ................................................................................ 35
3.3.7 Test Setup – CAN Data Collection ..................................................................... 36
3.3.8 Analysis Data Integration Test ........................................................................... 37
9
3.4 Conclusions ........................................................................................................... 40
Chapter 4 ............................................................................................................... 41
4 System Validation ............................................................................................. 41
4.1 Introduction .......................................................................................................... 41
4.2 Objectives ............................................................................................................. 42
4.3 Methods and Materials ........................................................................................ 42
4.3.1 Code and User Interface Develop for Measurements ...................................... 42
4.3.2 Storage Data Method........................................................................................... 42
4.3.3 Transducers .......................................................................................................... 43
4.3.4 Error Estimation and Test Setup- Acceleration ............................................... 44
4.3.5 Verification Measurement Instrument Calibration ......................................... 48
4.3.6 Error Estimation and Test Setup- Strain Gage ................................................ 49
4.3.7 Verification Measurement Instrument Calibration ......................................... 54
4.4 Results ................................................................................................................... 55
4.5 Conclusions ........................................................................................................... 58
Chapter 5 ............................................................................................................... 59
5 Summary and Conclusions ................................................................................ 59
5.1 General Conclusion .............................................................................................. 59
5.2 Contributions ....................................................................................................... 59
5.3 Future Work ......................................................................................................... 60
5.4 Recommendations ................................................................................................ 60
References .............................................................................................................. 61
Annexes ................................................................................................................. 63
Annex 1 ............................................................................................................................. 63
Annex 2 ............................................................................................................................. 66
Annex 3 ............................................................................................................................. 71
Annex 4 ............................................................................................................................. 75
Annex 5 ............................................................................................................................. 80
Annex 6 ............................................................................................................................. 87
Annex 7 ............................................................................................................................. 91
Annex 8 ............................................................................................................................. 96
Annex 9 ........................................................................................................................... 100
Annex 10 ......................................................................................................................... 101
Annex 11 ......................................................................................................................... 106
10
Annex 12 ......................................................................................................................... 108
Annex 13 ......................................................................................................................... 111
Annex 14 ......................................................................................................................... 117
Annex 15 ......................................................................................................................... 122
Appendix A ..................................................................................................................... 130
Appendix B ..................................................................................................................... 133
Appendix C ..................................................................................................................... 134
Appendix D ..................................................................................................................... 135
Appendix E ..................................................................................................................... 137
Appendix F ..................................................................................................................... 138
Appendix G .................................................................................................................... 140
Appendix H .................................................................................................................... 144
Appendix I ...................................................................................................................... 146
11
List of Tables
Table 1. Relevant Investigation. ........................................................................................... 18 Table 2. Standards related to Vibration Measurement Equipment. ...................................... 23 Table 3. Standards related to Vibration Measurement Equipment. ...................................... 24 Table 4. Commercial systems comparative [2]. ................................................................... 25 Table 5. Data Acquisition Software [2]. ............................................................................... 26 Table 6. Code width for pattern equipment and prototype. .................................................. 31 Table 7. Code width for pattern equipment and prototype. .................................................. 36 Table 8. Integration Test. - .tdms file analysis ..................................................................... 37 Table 9. Error sources for acceleration measurement. ......................................................... 46 Table 10. Prototype Theoretical Error for Acceleration Measurement. ............................... 46 Table 11. Prototype specifications for acceleration measurement ...................................... 49 Table 12. Prototype Theoretical Error for Strain Measurement. .......................................... 50 Table 13. Channels configuration for Strain Measurement. ................................................. 53 Table 14. Prototype specifications for strain measurement. ................................................ 54 Table 15. Prototype specifications for strain measurement with signal amplification. ....... 55 Table 16. Prototype specifications for acceleration measurement ...................................... 57 Table 17. Prototype specifications for strain measurement without signal amplification. . 57 Table 18. Prototype specifications for strain measurement with signal amplification. ....... 58
List of Figures
Figure 1. Measuring system for vibration validation by comparison to a reference
transducer........................................................................................................................ 24 Figure 2. General scheme for CAN connection [6] .............................................................. 27 Figure 3. Scheme of system development ............................................................................ 28 Figure 4. Hardware connections for Vibration Validation ................................................... 29 Figure 5. Configuration for electrical validation tests. ......................................................... 30 Figure 6. Measuring scheme for electrical validation by comparison. ................................. 31 Figure 7. Measuring system for electrical validation by comparison................................... 32 Figure 8. Display readings during tests. ............................................................................... 32 Figure 9. Graphic display with waveform obtained by the readings. ................................... 33 Figure 10. NI 9206 Electrical Error Analysis. ...................................................................... 34 Figure 11. SAE J1939 applications. ..................................................................................... 35 Figure 12. a) Pinout NI 9862 module, b) Pinout SAE J1939/13 adapter ............................. 36 Figure 13. Module recognized in NI MAX .......................................................................... 37 Figure 14. Plotted Parameters. - Engine Coolant Temperature ............................................ 38 Figure 15. Plotted Parameters. - Accelerator Pedal Position and Engine Speed .................. 39 Figure 16. Plotted Parameters. - Accelerator Pedal Position and Vehicle Speed ................. 39 Figure 17. Scheme of system implementation ..................................................................... 41 Figure 18 Accelerometer 2220-100 from Silicon Design.. .................................................. 43 Figure 19 Strain Gage – Linear Pattern from Micro Measurements. .................................. 44
12
Figure 20 Vibration system consisting of shaker and power amplifier. ............................... 45 Figure 21 Implementation of equipment for acceleration test. ............................................. 45 Figure 22 Error estimation for acceleration measurement. .................................................. 47 Figure 23 Equipment running acceleration test. ................................................................... 47 Figure 24 Error calculated at different frequencies. ............................................................. 48 Figure 25 Difference in the measurements versus pattern equipment.................................. 48 Figure 26 Voltage regulator circuit performed. .................................................................... 50 Figure 27 Quarter Bridge configured with Precision Resistors. ........................................... 51 Figure 28 Quarter Bridge configured with a Bridge Module. .............................................. 51 Figure 29 Strain Measurement Instrumentation. .................................................................. 52 Figure 30 Equipment running a strain simulation test. ......................................................... 52 Figure 31 Channels configuration in User Interface. ........................................................... 53 Figure 32. User Interface ...................................................................................................... 56 Figure 33 Method 2 for Storage Data.- Variable is written at the entered sampling
frequency. ....................................................................................................................... 56
13
Chapter 1
1 Introduction
Road load tests measure the transient and steady state inputs of a vehicle as it operates
over a road surface in the anticipated market region of use or over a replicated drive profile
on a test track. Road load measurements take into account all projected vehicle and driving
parameters such as mass, inertia, air and rolling resistance, road characteristics, engine loads,
and vehicle speed. Road load data is one of the best sources of fundamental information
necessary for analysis of the design, reliability, and structural integrity of vehicle
components. Data Acquisition (DAQ) system applied in the automotive field will allow to
know the behavior of the structure of the vehicle by modifications of components that
integrate it or for specific applications.
This study is focus on the heavy duty segment with Controller Area Network (CAN)
1939 protocol because they represent a great opportunity for the application of a DAQ
system.
If we refer to modifications of components of these units, by 2018 in Mexico the Euro
VI regulation will be implemented as indicated by the Ministry of Environment and Natural
Resources at NOM-044-SEMARNAT-2017 norm that sets the maximum limits allowed for
carbon monoxide (CO), nitrogen oxides (NOx), non-methane hydrocarbons (NMHC), non-
methane hydrocarbon plus nitrogen oxides (NMHC+NOx), particulate matter (PM) and
ammonia (NH3); the whole of them considered exhaust emission pollutants produced not
only by new diesel engines which will be used in vehicles with a gross vehicle weight over
3,857 kilograms, but also by heavy-duty vehicles with a gross. This implies changes in the
engine's displacement, to implement catalytic filters and others that modify the distribution
of loads on the chassis.
14
For special applications it is important to know the behavior of the structure, there
are case studies such as the “Measurement and Analysis of Vehicle Vibration for Bottled
Water Delivery Trucks” by Kyle Dunno from Department of Food, Nutrition, and Packaging
Sciences, Clemson University, Clemson , South Carolina, US that analyze the vibration
inputs experienced by the freight holding area of the vehicle because the distribution product
channels are subjected to three major categories of dynamic hazards: shock, vibration, and
compression.
Finally, according to the international recommendation concerned with vibration and
the human body ISO 2631, sets out limitation curves for exposure times from 1 minute to 12
hours over the frequency range in which the human body has been found to be most sensitive,
namely 1 Hz to 80 Hz. From these recommendations, it is interesting to note that in the
longitudinal direction, that is feet to head, the human body is most sensitive to vibration in
the frequency range 4 to 8 Hz. While in the transverse direction, the body is most sensitive
to vibration in the frequency range 1 to 2 Hz.
As described above, knowing the operating conditions of vehicles, especially
transport units, is of utmost importance.
1.1 Motivation
The main motivation is to develop technology that integrates external information
provided by the vehicle Electronic Control Unit (ECU) through additional sensors and
provide a tool to better understand the structural behavior according to the operation
conditions by analyzing the acquired data and allow feedback to the design phase to optimize
it if necessary.
1.2 Problem Statement
At present, there are equipment that allows the analysis of the information provided
by the ECU of units equipped with the CAN 1939 communication protocol and additional
15
sensors for acquiring signals of different parameters but separately. This means that in order
to obtain the information from the ECU, a specialized equipment is required, which should
be synchronized together with another equipment when acquiring the signals from the
sensors, this can generate a lag that could establish a false analysis if you want to have a
relationship between driving parameters and road conditions.
The specialized equipment for information of the ECU provides data in hexadecimal
language that must be treated in order to relate it to parameters such as rpms, motor
temperature, etc. and, on the other hand, there are modules for acquisition of vibration signals
but do not provide many channels for the analysis of the entire structure in the route tests.
It is important to have an easy-to-use, quick-connect and transportable equipment that
allows obtaining information from the ECU's unit as well as providing the greatest capacity
of channels for the connection of the sensors to acquire different signals according to the
desired parameters.
1.3 Thesis Hypothesis
It is possible to develop an easy-to-use, fast-connect and modular data acquisition
system that allows to take information from the ECU as well provide the most channels for
signal acquisition from different sensors that are connected according to the desired
parameters in order to give feedback to the quality and design departments.
1.4 Objective
The main objective is to validate the measurement capability of a compact data
acquisition prototype by performing experiments at laboratory level, also functional
integration between the system, the programmable application and instrumentation.
16
1.4.1 Specific Objectives
The objectives of this thesis are the following:
Select equipment to develop the prototype road load data acquisition (RLDA) system.
Develop the programmable application that allows acquire and storage the
information from the ECU with SAE 1939 protocol communication and analogical
signals from accelerometers and strain gages within the frequency range from 0 to 80
Hz.
Develop laboratory level experiments that allow to validate the repeatability,
reproducibility and reliability of the measurements as well as the good performance
of the selected equipment.
Establish a friendly and versatile user interface that allows the record of relevant
information for the unit’s conversion that must also be stored in a USB memory.
Set a self-calibration option or allow manual calibration of the setup of the connected
sensors.
Establish an operation manual for data acquisition equipment.
1.5 Thesis Content
This work is divided into 3 parts. In the first part the capabilities of the equipment
selected for the acquisition of the signals are disclosed and solutions are proposed for the
conditioning of the same since they must be within the frequency range of 0 to 80 Hz which
is the range of analysis for the selected application. The second part explains the
implementation of the data acquisition system for analog signals and CAN bus data collection
through laboratory tests with controlled parameters. Finally, vibration tests were designed
and the validation of results was carried out by a repeatability and reproducibility analysis.
The methodology that describes the steps followed in each stage of the project with
the purpose of establishing tests in a methodical way and validating the repeatability and
reliability of the data is presented in chapters 3 and 4.
17
1.6 Thesis Scope
The thesis scope is defined below:
System capability and Instrumentation. - It is important to establish the scope of the
equipment as well as to define the types of compatible sensors according to the
frequency range defined from 0 to 80 Hz.
Frequency Analysis. - It is important, for the defined frequency range, to establish
the sampling frequency of the DAQ system as well as signal conditioning.
Laboratory Tests. - Define the control parameters to establish the laboratory tests
since it is important to analyze the behavior of the measurement system and guarantee
repeatability in the measurements.
Validation and calibration of the System. - The equipment calibration method is
established by direct comparison to analyze the reliability of the data provided by the
prototype.
Validation of information storage. - Simulating readings of CAN parameters of data
acquired from a truck, the real-time measurement of sensors is carried out at the same
time, once the tests have been completed, validate that the necessary information has
been stored for the subsequent analysis according to the type of test performed.
18
Chapter 2
2 Literature Review
In this chapter the literature review, state of art of main topics, available technology
and methodology for project development is presented. More information about data
acquisition system in Annexes 1 to 4.
2.1 State of Art
This section discloses most relevant publications of the main topics covered in this
project considering the research area. The following table shows a detail of the works that
will be discussed below.
Table 1. Relevant Investigation.
Field Year Author Title
DAQ
System
2017 R. C. Treviño
Road Load Data Acquisition system Through
Real-Time technology: Validation and First
Experiments.
2013 R. Rajamani Instrumentation of Navistar Truck for Data
Collection.
2007 L. Alvarez, R.
Henao and E. Duque
Analog Filtering Schemes Analysis for ECG
Signals.
2002 A. Gani and M. J. E.
Salami
A LabVIEW based Data Acquisition System for
Vibration Monitoring and Analysis.
CAN
Bus Data
Collection
System
2017 A. Ramirez Development of interface for reading and storage
CAN parameters under SAE -1939 standard.
2015 S. E. Marx
Controller Area Network (CAN) Bus J1939 Data
Acquisition Methods and Parameter Accuracy
Assessment Using Nebraska Tractor Test
Laboratory Data.
19
2.1.1 DAQ System
1.- “A LabVIEW based Data Acquisition System for Vibration Monitoring and
Analysis” [1]: This article presents Labview as an easy-to-use platform with a graphical
programming environment that covers the three main components of a DAQ system that are
data acquisition, data analysis and instrument control.
The LabVIEW (Laboratory Virtual Instrument Engineering Workbench) full
development system features the analysis library. The function in this library is called virtual
instrument (VIs). These VIs allow to use classical processing algorithms without writing a
single line of code. The LabVIEW block diagram approach and the extensive set of analytical
VIs simplify the development of analysis applications.
For signal processing, using LabVIEW, it is necessary to convert the analog signal
into a digital representation. In practice this is done through an analog-digital converter
(A / D) considering the Nyquist theorem to determine the sampling rate and thus avoid
aliasing.
2.- “Road Load Data Acquisition System Through Real-Time Technology: Validation
and First Experiments” [2]: This thesis presents a reliability study for a DAQ system
prototype based on LabView. The fundamental concepts for developing a DAQ system are
presented as well as a selection analysis of equipment available in the market.
The prototype provides 24 measurement channels and the measured magnitude of
interest is acceleration. For the analysis carried out, Software LabView and Hardware
Compact-RIO 9030 with NI 9205 voltage input modules were the components for the DAQ
system. The instrumentation was performed by MEMs accelerometers.
The laboratory tests were performed in a simulated vehicle room (QoV), the code in
LabView was implemented with the FPGA module of the cRIO 9030 with a sample rate of
20
1000 samples per second to then analyze the reliability of the equipment through two
statistical methods (Anova and Wheeler's).
3.- “Instrumentation of Navistar Truck for Data Collection” [3]: This main goal of
this project was to instrument a Navistar truck with a suite of sensors and developed a data
acquisition system for recording sensor signals. The truck was instrumented with 20
accelerometers, including accelerometers on the axles of the tractor and the trailer and on the
bodies of the tractor and the trailer. A cRIO-based data acquisition system, a rugged laptop
and Labview software together serve as a flexible platform for data acquisition.
This report provides samples of some recorded data and also includes a user manual
for use of the data recording software on the truck. Two types of accelerometers were
purchased from Analog Devices: ADXL335Z accelerometers with +/- 3g measurement range
(for use on the tractor and trailer bodies) and ADXL325Z accelerometers with +/- 5g range
(for use on the axles). It is important to note that the acceleration values on the axles that
were measured occasionally exceed 2 g on Minnesota Roads at speeds of 50 mph or higher.
Notes further that since a rougher road can cause higher accelerations, a range of +/- 3g was
felt to be inadequate for axle acceleration measurements.
4.- “Analog Filtering Schemes Analysis for ECG Signals” [4]: This paper presented
a characterization of the electrocardiographic signal in order to comprehend how to obtain it,
its origins and its components, as different stages of the cardiac cycle. Besides, there are
described and simulated different kinds of perturbations affecting electrocardiographic
signals. In practice, there are presented designs and implementations of band-pass analog
filters connected as a cascade of lowpass and high-pass filters, aiming to eliminate several
well-known perturbations distorting electrocardiographic signals.
In this case they applied characteristic noise of the ECG signals to a clean signal. A
Butterworth band pass filter, which is the best flat response, was used by operational
amplifiers TL084 and LM234. Then, using a PCI-6221 DAQ system from National
Instruments, they programmed the acquisition of 1000 samples with a sampling frequency of
21
500 Hz to compare the original signal and the filtered signal using the Mean Square Error
(MSE).
Given the frequency range of the ECG signal (0.05Hz -100Hz) and (0.025Hz - 50Hz),
they conclude that the band-pass filter is the best option to filter the undesirable noises that
appear in these signals and that under these conditions, of all the filters, the pass band of
order 6 (0.05Hz-100Hz) was the one that obtained the best filtering response.
2.1.2 CAN BUS Data Collection System
1.- “Controller Area Network (CAN) Bus J1939 Data Acquisition Methods and
Parameter Accuracy Assessment Using Nebraska Tractor Test Laboratory Data” [5]: This
thesis presents the implementation of a data acquisition system under CAN 1939 protocol in
two sections that will be explained below:
“Comparing Various Hardware/Software Solutions and Conversion Methods for
Controller Area Network (CAN) Bus data collection”, study was performed to determine if
there was a difference in the data collected from these various data acquisition solutions, and
to quantify those differences.
Two types of data were observed for this study with two different hardware options,
a NI CompactDAQ 9862 and a Vector CANcaseXL. The first data type was CAN bus frame
data, where a data point is collected for each line of hex data sent from the ECU. One problem
with frame data is the resulting large file sizes, therefore a second data type collected was an
averaged signal or waveform data.
The resulting difference was less than .0025 RPM for engine speed comparisons, zero
for fuel rate and fuel temperature comparisons, and the mean percent difference was less than
.08% between the methods of data collection.
22
“Validation of machine CAN Bus J1939 fuel rate accuracy using Nebraska Tractor
Test Laboratory fuel rate data”, A pilot study was performed to determine if there were
differences between data collected using the machine controller area network (CAN) bus
Society of Automotive Engineers (SAE) J1939 standard fuel rate and data collected from a
physical measurement system utilized by the Nebraska Tractor Test Laboratory (NTTL). The
pilot study concluded that there was a difference between the data (up to a 6.22% error),
which indicated a need to perform further studies on this comparison.
The goal of this study was to compare fuel rate values collected from the CAN bus to
the physically measured fuel rate value from tractor performance tests conducted at the
Nebraska Tractor Test Laboratory (NTTL). The fuel rate values were collected
simultaneously and then synchronized to confirm accuracy of results. Fuel rate, as recorded
from the CAN bus, resulted in a ±5% error of actual physically measured fuel rates. Error for
higher fuel rates within the torque curve were closer to ±1%.
2.- “Development of interface for reading and storage CAN parameters under SAE -
1939 standard” [6]: This thesis presents a versatile, reliable and efficient interface using
National Instruments hardware and through the SAE J1939 CAN protocol to manage
communication with the heavy vehicle ECU´s to visualize, decode and store parameters
requested by the automotive industry.
Due to its processing capability, dimensions, modules and price, the DAQ cRIO 9030
system is used with the NI 9862 module. The programming was done in Labview and,
because the parameters that are going to be read (Engine Speed, Accelerator Pedal Position,
Vehicle Speed and Engine Coolant Temperature) are generated at a different frequency, the
code was modified to avoid gaps when relating them, for this the module was connected to a
truck under the J1939 protocol considering the necessary configuration for this in both
hardware and software.
Finally, after acquiring the data through the National Instruments equipment, a
reading comparison is carried out using the CANalyser equipment, which concludes that the
23
selected equipment has compatibility with the J1939 protocol and that the system is stable at
the time of taking readings with a variation 2.5% compared to CANalyser, which is a OEM
equipment.
2.2 Standards
The standards related to vibration measurement equipment were considered as the
basis for the development of the application, the most important topics are detailed below:
Table 2. Standards related to Vibration Measurement Equipment.
Standard Year Title
BS ISO 4866 2010
Mechanical vibration and shock - Vibration of fixed
structures - Guidelines for the measurement of vibrations
and evaluation of their effects on structures.
IS ISO 13373 2005
Condition monitoring and diagnostics of machines -
Vibration condition monitoring - Part 2 Processing, analysis
and presentation of vibration data.
IS ISO 8041 2005 Human response to vibration - Measuring instrumentation.
IS ISO 16063 2003
Methods for the calibration of vibration and shock
transducers - Part 11.- Primary vibration calibration by laser
interferometry
More details about these standards in Annex 5.
2.2.1 Tolerance of Vibration Measurement System
From IS ISO 8041 standard, the relative error tolerances allowed for a vibration
measurement system are presented in the following table.
24
Table 3. Standards related to Vibration Measurement Equipment.
Parameter Tolerance
Tolerance of the electrical part of the instrument ± 2 %
Tolerance of the vibration transducer response ± 3 %
Tolerance of indication at the reference frequency
under reference environmental conditions ± 5 %
2.2.2 Vibration calibration by comparison to a reference transducer
The calibration procedure of rectilinear vibration transducers by comparison is
specified in ISO 16063 standard. Below is a diagram of the measurement system to perform
calibration by comparison to a reference transducer.
Key
1 Signal generator 3 Shaker 5 Prototype
2 Amplifier 4 Filter 6 Pattern equipment
7 Reference transducer
Figure 1. Measuring system for vibration validation by comparison to a reference transducer
25
2.3 Summary
The present investigation will be based on the following topics highlighted in the
literature review.
- From the research carried out by R. Cárdenas [2], thanks to the price analysis of
different data acquisition systems that are in the market, it was considered to use
the equipment and software selected in this investigation to develop the prototype.
The analyzes are presented in Tables 4 and 5.
- From this work [2] it is also considered to implement a 40 Hz low pass filter and
validate if that is the best option to avoid signal noise.
- - Finally, in this research [2] the R & R study is greater than 10%. It is important
to identify the sources of uncertainty to reduce them to ≤ 5%.
Table 4. Commercial systems comparative [2].
Note: Prices consulted in March, 2016
26
Table 5. Data Acquisition Software [2].
Note: Prices consulted in March, 2016
- From the research carried out by Armando Ramírez [6], the selected parameters
of accelerator pedal position, engine speed, engine coolant temperature and
wheel-based vehicle speed are considered for the analysis to determine driving
conditions that have a relationship with the response to road conditions on the
tuck structure.
- The NI 9862 module will be used, together with the cRIO-9030 equipment and
LabVIEW software, to decode the parameters selected under the SAE J1939
standard from the ECU's truck and presented in a friendly way, unlike other
equipment such as CANanalyser from Vector manufacturer [6] that, although
contain greater functions, require a high level of training and the generated data
are stored in special files, which implies higher costs of additional software and
often do not allow modify or adapt the application to the real need. Figure 2 shows
a connection scheme to obtain the parameters from the ECU's truck.
- Finally, to develop the application of DAQ system, the code developed in this
research [6] will be replicated to take the parameters from the ECU and adapted
to the new code for the data acquisition from the different analog sensors.
27
Figure 2. General scheme for CAN connection [6]
Chapter 3
3 System Implementation
3.1 Introduction
This chapter describes the implementation of data acquisition system for both CAN
parameters and analog signals. The data acquisition system consists of Hardware and
Software. The hardware is composed by the cRIO-9030 equipment with 3 NI 9206 modules
for voltage measurement (analog signals) and a NI 9862 module for acquiring CAN data.
Programming is developed with LabVIEW software. Figure 3 below shows a diagram of the
system implementation.
28
Figure 3. Scheme of system development
3.2 Objectives
o Perform the electrical validation to know the deviation of the results.
o Perform the validation of CAN parameters integrated to the data acquisition code.
o Verify the deviation of the sampling frequency in .tdms file generated.
3.3 Methods and Materials
This part describes how to verify the uncertainty from analog signals, validate the
CAN parameters decoded and check this data in .tdms format file generated.
3.3.1 Hardware and Software Configuration
Considering ISO 8041 Standard, the calibration verification of the cRIO 9030 (see
specifications in Appendix A) equipment is carried out in the electrical part to validate that
the error in the measurement is less than 2% using the direct comparison method with a
pattern equipment.
Analog Signal
• Electric Error Validation
CAN Signal
• Decode Validation
Storage• File
Validation
29
Hardware. -
The connection of the cRIO 9030 equipment was carried out together with the NI
9206 and NI CAN modules. The instrumentation must consider the connection to each
channel making use of instrumentation cable of the Belden brand, 9534 series of 15 meters
in length, this due to the focus application of the current project.
Figure 4. Hardware connections for Vibration Validation
The signal generator B & K Precision model 4011A (specifications in Appendix B)
was connected in parallel to the pattern equipment B & K model 3160A (specifications in
Appendix C) and to the channels of the modules to then perform the analysis of the data.
Software. -
For the data acquisition with the cRIO 9030 equipment, LabVIEW 2015 software was
used while the PULSE Time Data Recorder software was used for the pattern equipment.
The code for data acquisition and CAN parameters was generated independently to validate
the acquired information, which is detailed below.
30
3.3.2 Software application for Electrical Validation
For the development of the application, the programming was done using the
LabVIEW Real Time tool since it is based on single-point I / O data and the required loops
rates do not exceed 500 Hz. When configuring the properties of Real Time CompactRIO, it
can show that an acquisition can be made with a sampling period of 1 ms, that sampling
frequency could reach up to 1000 samples per second in a stable manner. 800 samples per
second will be the sampling frequency, this will take 10 times more samples what is
recommended in practice [7].
Figure 5. Configuration for electrical validation tests.
It is very important to keep in mind the resolution of the equipment. The pattern
equipment has a resolution of 24 bits and a measuring range of +/- 10 V while the module
9205 has a resolution of 16 bits and will be implemented with a measuring range +/- 5 V.
With this information making use of equations 1 and 2, the code width of the analog signal
was obtained for each equipment.
# 𝒐𝒇 𝒍𝒆𝒗𝒆𝒍𝒔 = 𝟐𝑹𝒆𝒔𝒐𝒍𝒖𝒕𝒊𝒐𝒏 (1)
𝑪𝒐𝒅𝒆 𝒘𝒊𝒅𝒕𝒉 =𝑫𝒆𝒗𝒊𝒄𝒆 𝑰𝒏𝒑𝒖𝒕 𝑹𝒂𝒏𝒈𝒆
𝟐𝑹𝒆𝒔𝒐𝒍𝒖𝒕𝒊𝒐𝒏 (2)
31
Table 6 shows the results of the calculations, the standard equipment presents a
resolution 128 times greater than that of the prototype, in addition the sampling frequency of
the standard equipment will be 1.6 KHz, this is twice the sampling frequency of the
prototype. The foregoing is established to guarantee the reliability and repeatability of the
tests as well as a correct evaluation of the accuracy when the instrumentation is implemented.
Table 6. Code width for pattern equipment and prototype.
Pattern 24 bits Prototype 16 bits
# of levels 1677216 65536
Code width 1.2 μV 164.2 μV
Once the acquisition and storage method has been established in both equipment, the
tests for the electrical and sampling frequency evaluation are configured.
3.3.3 Test Setup – Electrical Evaluation
For this test, the B & K Precision model 4011A signal generator will be used within
the range of 0.4 to 80 Hz. The pattern equipment B & K model 3160A will be connected in
parallel to the prototype and then perform an error analysis. Figure 6 shows a connection
scheme while Figure 7 shows the system implemented for this test.
Key
1 Signal generator 2 Prototype 3 Pattern equipment
Figure 6. Measuring scheme for electrical validation by comparison.
32
Figure 7. Measuring system for electrical validation by comparison.
In figures 8 and 9, the help screens of the implemented code can be viewed. Figure 8
allows to see the live readings and at the end a statistical summary with the obtained data
while figure 9 allows to visualize the curve generated with the readings generated in real
time.
Figure 8. Display readings during tests.
33
Figure 9. Graphic display with waveform obtained by the readings.
With the help of Navistar, who provided a vibration report of one of its units in
Colombia, was possible to analyze it and validate that the maximum voltage output amplitude
of the transducers used in the test was less than 1 V. For electrical validation, the value of 1
V amplitude of a sine wave will be set at the output of the generator and 3 tests will be carried
out for each selected frequency within the analysis range (0.4, 5, 10, 20, 30, 40, 50, 60, 70
and 80 Hz). From each test the R.M.S. calculation is performed to determine the amplitude
of the readings of both equipment (pattern and prototype). The analysis is done with
spreadsheets in Excel. To determine the error, equation A5 1 (Annex 5) is applied. The error
must not exceed 2%.
3.3.4 Analysis of Electrical Validation Tests
In Figure 10 the results of the error analysis at different frequencies is exposed for the NI
9206 module.
34
Figure 10. NI 9206 Electrical Error Analysis.
After the test it was possible to determine that the error generated from 0 to 5 Hz is
less than 0.4% while from 5 to 80 Hz the error is less than 0.1%. This result is allowed to be
below the 2% specified in the ISO 8041 standard.
3.3.5 Software application for CAN J1939 data
The code implemented within the thesis "Development of interface for reading and
storage of CAN parameters under the SAE 1939 standard" by Armando Ramirez [6], was
taken as a reference.
This protocol provides one language across manufactures for different applications.
In contrast, passenger cars typically rely on manufacturer specific protocols.
Heavy-duty vehicles (e.g. trucks and buses) is one of the most well-known
applications. However, several other key industries leverage SAE J1939 today either directly
or via derived standards (e.g. ISO 11783, MilCAN, NMEA 2000, FMS):
Foresting machinery (e.g. delimbers, forwarders, skidders, ...)
Mining vehicles (e.g. bulldozers, draglines, excavators, …)
Military vehicles (e.g. tanks, transport vehicles, …)
Agriculture (e.g. tractors, harvesters, …)
35
Construction (e.g. mobile hydraulics, cranes, …)
Fire & Rescue (e.g. ambulances, fire trucks, …)
Many other (e.g. ships, pumping, power generation, ...)
Figure 11. SAE J1939 applications.
Figure 11 shows several applications of the SAE J1939 protocol. In this project
Navistar provided support and testing were performed on an International truck model Pro
Star. For the laboratory tests, data from a test performed were stored as a constant, which
will be used to simulate the signal that will be decoded according to the requested parameters.
3.3.6 Data Collection Integration
The parameters to be stored are engine speed, accelerator pedal position, wheel-based
vehicle speed and engine coolant temperature. The data frequency transmission of these
parameters varies, this can be evidenced in SAE J1939-71 standard. Table 7 shows the period
and sampling frequency to be defined for the acquisition of the parameters.
36
Table 7. Code width for pattern equipment and prototype.
Parameter Transmission
Repetition Rate
Sample Frequency
Engine Speed 50 ms 20 sample/ second
Acelerator Pedal Position 50 ms 20 sample/ second
Wheel-Based Vehicle Speed 100 ms 10 sample/second
Engine Coolant Temperature 1 s 1 sample/second
Since the sampling frequency of these parameters is much lower than the sampling
frequency of the accelerometers, and to keep a relation between them, the last value obtained
in the different frequencies is considered and repeated until a new one is obtained.
For this test, a measurement channel was enabled within the programming to verify
the decoded data of the stored CAN frame and the established sampling frequency.
3.3.7 Test Setup – CAN Data Collection
The configuration of the NI 9862 module was carried out according to what is
indicated in the manual. It is important to note that this module requires external power for
its operation. Figures 12a and 12b show the configuration of the pins for both the SAE adapter
and the NI 9862 module.
a) b)
Figure 12. a) Pinout NI 9862 module, b) Pinout SAE J1939/13 adapter
NI MAX software is used to visualize if the CAN module has been recognized.
37
Figure 13. Module recognized in NI MAX
Finally, it is necessary to create a virtual session in LabVIEW to interact with the NI
9862 module. Details of this configuration in Annex 6.
A road test was performed on a ProStar truck from Navistar, the test lasted
approximately 5 min and the reading of all test was stored as a variable. This variable is used
to simulate the CAN reading in the following tests. With CAN simulation, the generated
.tdms file will be analyzed to validate the data storage frequency of both, the type of
transducer and the selected CAN parameters.
3.3.8 Analysis Data Integration Test
Table 8 presents a report of the analysis of the test carried out where for each channel
the type of data, number of samples, the test time and the sampling frequency that is
calculated are shown.
Table 8. Integration Test. - .tdms file analysis
Group Channels Description
DATA 6 Data Integration Test
DATA
Channel Datatype Samples Test time (s) Sampling
Frequency
Time (s) DT_DOUBLE 245070 308.9711781 793
Engine Speed (RPM) DT_DOUBLE 245070 308.9711781 793
Accelerator Pedal Position (%) DT_DOUBLE 245070 308.9711781 793
Vehicle Speed (Km/hr) DT_DOUBLE 245070 308.9711781 793
Engine Coolant Temperature (Celcius) DT_DOUBLE 245070 308.9711781 793
Sensor 1 (V) DT_DOUBLE 245070 308.9711781 793
38
For the sampling frequency error, the equation A5 1 (Annex 5) is used and the
reference is 800 samples per second. The calculated error was -0.9%, that is, of each 100
samples the equipment loses approximately one.
On the other hand, when the CAN parameters are plotted, it can be verified that there
is coherence in the information presented since there is a correct relationship between the
position of the accelerator pedal and the engine RPMs, as well as a relationship between the
position of the accelerator and the truck speed. The operating temperature of the engine
remained constant near 80 Celsius degrees which is within the operating parameters of a
diesel internal combustion engine.
Figure 14. Plotted Parameters. - Engine Coolant Temperature
Figure 15 shows the position data of the Accelerator Pedal vs the Engine RPMs. In
order to better visualize this relationship, the pedal position data has been multiplied by 10.
It can be clearly seen the response of the motor with the position of the pedal when
accelerating the motor during the time of the test.
39
Figure 15. Plotted Parameters. - Accelerator Pedal Position and Engine Speed
Likewise, it is possible to visualize that as the throttle position is maintained, the unit
gains speed and can even appreciate interruptions this curve that could be the time intervals
between changes in transmission so one could infer a correct coherence between the decoded
data, this can be seen in figure 16.
Figure 16. Plotted Parameters. - Accelerator Pedal Position and Vehicle Speed
40
3.4 Conclusions
o Electrical validation. - it was possible to determine that the error generated from 0
to 5 Hz is less than 0.4% while from 5 to 80 Hz the error is less than 0.1%. This
result is allowed to be below the 2% specified in the ISO 8041 standard.
o Validation of CAN parameters integrated to the data acquisition code. - It was
possible to run the program and verify the data acquisition as well as the decoding
of the parameters coming from the CAN frame in real time and that are consistent
with the test performed.
o Sampling frequency. - In the .tdms file it was possible to verify that there is an error
of 0.9%. This is acceptable and considering that 10 times more data is being taken
for a correct analysis within the range of 0 to 80 Hz. The loss of one data per hundred
is not significant.
o The prototype complies with the project requirements for data acquisition.
41
Chapter 4
4 System Validation
4.1 Introduction
This chapter describes the implementation of the data acquisition system for the
measurement of acceleration and strain with 24 channels enabled. A friendly and efficient
user interface was developed that also allows the acquisition of CAN parameters under J1939
protocol. For the acceleration measurement, MEMS accelerometers will be used from Silicon
Design model 2220-100 while a strain gage will be used for the strain measurement from
Vishay Micro-Measurements model CEA-06-125UN-350. Laboratory tests will be carried
out to validate the error in the measurements versus measurements with the equipment used
as pattern B&K 3160A. Figure 17 below shows a scheme of the system implementation.
Figure 17. Scheme of system implementation
Acceleration
•Error
•Calibration
Strain
•Error
•Calibration
Storage
•File Validation
42
4.2 Objectives
o Develop a friendly and reliable user interface for data acquisition.
o Perform a modular code for channel expansion of analog signals.
o Develop signal conditioning for acceleration and strain instrumentation.
o Perform tests with accelerometers and strain gages to validate the measurement
error.
o Verify the data storage.
4.3 Methods and Materials
This part describes how code was developed considering the expansion of the
channels as well as how the instrumentation was performed with accelerometers and strain
gages, as well as the conditioning of their signals.
4.3.1 Code and User Interface Develop for Measurements
For the development of the code, it was intended to present the information in simple
way and oriented for the user, for these reasons in the main screen 5 tabs are presented.
Details of the code and user interface in Annex 7.
4.3.2 Storage Data Method
Two methods were tested to store the information. The method where the sampling
frequency depends on the time period for writing in the .tdms file was selected, because
allows to relate the measurement of the transducers with the last reading of each selected
parameter of the CAN module. Details of methods for data storage implemented in Annex 8.
43
4.3.3 Transducers
Acceleration
Since the NI 9206 module allows the reading of voltage changes, the transducers that
can be used for this application are MEMS type. Piezoelectric transducers are discarded due
to the type of power required for their operation. The search for accelerometers of different
manufacturers was carried out and then several options of different manufacturers are
presented Annex 9.
For acceleration laboratory tests the transducer from Silicon Design model 2220-100
will be used. This is a low frequency accelerometer that allows to measure accelerations in a
range of 100 g with a power range of 12 to 32 V which could supply a truck depending on
the electrical system (12 or 24V). The signal of the measurement made with a differentiated
connection is ±4 V. Detailed information on this transducer can be found in Appendix D.
Figure 18 Accelerometer 2220-100 from Silicon Design..
Strain Gages – Linear Pattern
For the selection of the strain gage, the Strain Sensor Reference Guide from Micro
Measurements was followed. It is important to keep in mind the material on which the gage
will be placed as well as work cycles, accuracy required and among other parameters that are
mentioned in the guide [8]. It is also important to mention the conditioning of the signal and
the necessary components to achieve this conditioning depends on the selected strain gage.
44
Figure 19 Strain Gage – Linear Pattern from Micro Measurements.
For the laboratory tests, the parameters of the strain gage model CEA-06-125UN-350
was considered, which have application gage on metallic surface that correspond to 350
Ohms ± 0.3%. The strain range of these strain gages is ±5%. Detailed information about this
transducer can be found in Appendix E.
4.3.4 Error Estimation and Test Setup- Acceleration
For this test, the B&K Precision signal generator model 4011A will be used to
generate sine waves to simulate vibrations that will be amplified with the LDS equipment
model PA500 to operate the LDS shaker model V555, specification in Appendix F. The B&K
module model 3160A together with the Pulse Data Recorder software will be used as pattern
measurement equipment.
45
Figure 20 Vibration system consisting of shaker and power amplifier.
The pattern equipment has a resolution of 24 bits which allows detecting voltage
changes of 1.2 μV, in addition, the Pulse Data Recorder software allows to define the
sampling frequency that in our case will be twice the frequency of the prototype and then
apply the method by comparison.
Figure 21 Implementation of equipment for acceleration test.
46
The prototype for the measurement with transducers uses NI 9206 modules for which,
within the specifications (Appendix G), the manufacturer presents formulas for estimating
the error. The calculation of the error is made according to the measuring range configured
in the module. Details of error estimation for this test in Annex 10.
The sources of error considered to estimate the total error in the measurement with
the selected accelerometers are presented in the table.
Table 9. Error sources for acceleration measurement.
Source Range Magnitude Error (%)
Módulo 9206
< 1 G > 8
1 to 1.5 G 5 to 8
1.5 to 3 G 5 to 3
> 3 G < 3
RC Filter 80 Hz < 2.5
Accelerometer ±65 G 1 to 2
Since the accelerometer error is something inherent to the sensor, the focus will be on
the error produced by the sampling frequency and the module. Keeping in mind that at low
frequencies we expect low accelerations and as the frequency increases the acceleration
increases, therefore is important to consider the error of the module 9206. Combining the
errors, would have the following:
Table 10. Prototype Theoretical Error for Acceleration Measurement.
Theoretical Error Range (g) Error (%)
Prototype
< 1 > 10
1 to 1.5 7 to 10
1.5 to 3 3 to 5
> 3 < 3
47
Figure 22 Error estimation for acceleration measurement.
The RC filter was implemented in the signal and the measurement was carried out
with the 16 available channels of the NI 9206 module.
Figure 23 Equipment running acceleration test.
After the tests, the analysis of the signals obtained was performed to validate the error
in relation to the pattern equipment.
48
4.3.5 Verification Measurement Instrument Calibration
Using Excel, the measurements taken in mV were converted to g, this first to check
the error for the electrical signal and then discard some error in the programming. The graphs
below allow us to see the behavior of the readings of the 16 channels in the tests carried out
at different frequencies. The measurement analysis for this test in Annex 11.
Figure 24 Error calculated at different frequencies.
Figure 25 Difference in the measurements versus pattern equipment.
49
In general, the error of the measurements in acceleration will go from -0.1 to -0.2 g
within a range of 0 to 80 Hz according to the tests carried out. The specifications of the
prototype with the selected equipment and instrumentation implemented are shown in table
11.
Table 11. Prototype specifications for acceleration measurement
Prototype Frequency Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low Pass Filter
Fc 338 Hz
Silicon Design Accelerometer model
2220-100
0 to 80 Hz 0.1 g -0.1 g
máx -0.2 g
4.3.6 Error Estimation and Test Setup- Strain Gage
The exactitude calculated for the NI 9206 module within the ± 5V scale is considered.
This accuracy is important to relate to the measurement range of the strain gages. It is known
that the deformation allowed for the strain gage is 5% and to perform the measurement with
strain gage it is recommended to use a Wheatstone bridge to detect a voltage change with the
variation of one of the resistances that are part of the bridge. Details of error estimation for
this test in Annex 12.
. The following table shows the expected error in different measurement ranges,
which will be evaluated by simulating the behavior of a strain gauge with a variable
resistance.
50
Table 12. Prototype Theoretical Error for Strain Measurement.
Theoretical Error Strain Range
(%)
Error
(%)
Prototype
< 1 > 10
1 to 2 5 to 10
2 to 5 < 5
Is important to perform a voltage regulator, for this the LM 7805 transistor is used
with the manufacturer recommended circuit (Appendix H). The circuit was made and
verified, the output voltage was 5 ± 0.1 V. The following image shows the test performed to
validate this.
Figure 26 Voltage regulator circuit performed.
The Wheatstone bridge may be accomplished using precision resistors or using
modules manufactured by Micro Measurements [9].
51
Figure 27 Quarter Bridge configured with Precision Resistors[9]..
Figure 28 Quarter Bridge configured with a Bridge Module [9]..
The MR1-350-172 module from Micro Measurements was selected to perform the
quarter bridge configuration and to simulate the signal a variable resistance model 89PR100
is used, specifications in Appendix I. Figure 29 shows the instrumentation implemented for
strain measurement.
52
Figure 29 Strain Measurement Instrumentation.
Once the circuit was implemented, the measurement was carried out with 3 prototype
channels and as a pattern, there were two equipment: B&K 3160-A and the multimeter
MUL-280.
Figure 30 Equipment running a strain simulation test.
Quarter Bridge
Module
Variable
Resistor
Voltage
Regulator
53
The configuration of the 3 channels of the prototype are presented in the table below.
Table 13. Channels configuration for Strain Measurement.
Parameter Channel 1 Channel 2 Channel 13
Transducer Other Other Strain Gage
Sensivity 1 1 2.155
Calibration No Yes No
Units Volts Volts % Strain
The information presented in the previous table was introduced in the user interface
before starting the test. The following image shows the channels enabled to perform the
measurement.
Figure 31 Channels configuration in User Interface.
After the tests, the analysis of the signals obtained was performed to validate the error
in relation to the pattern equipment.
54
4.3.7 Verification Measurement Instrument Calibration
While the program is running, using the graph of channel 13, measurements are made
with variations of approximately 1% strain, and then the signals measured directly with
channel 1 are analyzed. The measurement analysis for this test in Annex 13.
In general, the error of the measurements in strain will be ±0.1 %ɛ in a strain range
of ± 5% according to the tests carried out. The specifications of the prototype with the
selected equipment and instrumentation implemented are shown in table 14.
Table 14. Prototype specifications for strain measurement.
Prototype Strain Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low pass Filter
Fc 338 Hz
Voltage Regulator LM
7805
Micro Measurements MR1-350-172 module
Micro Measurements
CEA-06-125UN-350 Strain Gage
± 5 % of ɛ ± 50000 μɛ
0.1 % of ɛ 1000 μɛ
± 0.1 % of ɛ ± 1000 μɛ
After analyzing the resolution of the equipment for strain measurements without
amplifying the signal, the report of the unit tested by Navistar in Colombia was reviewed and
it could be seen that the sensitivity of the gauges implemented in that truck was 50 mV / ɛ.
The resolution considered for these measurements was 10 μV, that is ± 200 μɛ.
55
With the aforementioned, the 1000 μɛ resolution of the prototype should be improved
and a solution for this is to amplify the signal. Keeping in mind the resolution of 200 μɛ from
Navistar report, with a gain of 10: 1, the minimum output signal of the bridge would be 10
times higher so that the resolution of prototype would now be 0.01% strain or 100 μɛ. The
measurement analysis for strain test with signal amplification in Annex 14.
In general, the error of the measurements in strain will go from ±0.01 %ɛ in a strain
range of ± 3% according to this instrumentation. The specifications of the prototype with the
selected equipment and instrumentation implemented are shown in next table.
Table 15. Prototype specifications for strain measurement with signal amplification.
Prototype Strain Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low pass Filter
Fc 338 Hz
Voltage Regulator LM 7805
Micro Measurements MR1-350-172 module
Micro Measurements CEA-06-125UN-350 Strain Gage
Operational Amplifier
INA114BP G = 11
± 3 % of ɛ ± 30000 μɛ
0.01% of ɛ 100 μɛ
± 0.01 % of ɛ ± 100 μɛ
4.4 Results
A user interface was generated that allows measurement of acceleration, strain and
voltage, as well as parameters from the ECU under CAN 1939 protocol.
56
Figure 32. User Interface
Two methods were established for the storage of the information, and the one that
allows to integrate and save CAN and sensor data at the same time was selected since the
sampling frequency is determined by the storage period of the variables in the .tdms file.
Figure 33 Method 2 for Storage Data.- Variable is written at the entered sampling frequency.
57
For the acceleration measurement, tests with MEMS accelerometers were established
and the precision of the equipment with the selected instrumentation could be validated.
Table 16. Prototype specifications for acceleration measurement
Prototype Frequency Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low Pass Filter
Fc 338 Hz
Silicon Design Accelerometer model
2220-100
0 to 80 Hz 0.1 g -0.1 g
máx -0.2 g
For the strain measurement, tests with strain gages were established and the accuracy
of the equipment could be validated with 2 options in the instrumentation: without signal
amplification and with an 11: 1 gain of the signal.
Table 17. Prototype specifications for strain measurement without signal amplification.
Prototype Strain Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low Pass Filter
Fc 338 Hz
Voltage Regulator LM
7805
Micro Measurements MR1-350-172 module
Micro Measurements
CEA-06-125UN-350 Strain Gage
± 5 % of ɛ ± 50000 μɛ
0.2 % of ɛ 1000 μɛ
± 0.1 % of ɛ ± 1000 μɛ
58
Table 18. Prototype specifications for strain measurement with signal amplification.
Prototype Strain Range Resolution Accuracy
NI cRio -9030 NI 9206 module
RC Low Pass Filter
Fc 338 Hz
Voltage Regulator LM 7805
Micro Measurements MR1-350-172 module
Micro Measurements CEA-06-125UN-350 Strain Gage
Operational Amplifier
INA114BP G = 11
± 3 % of ɛ ± 30000 μɛ
0.01% of ɛ 100 μɛ
± 0.01 % of ɛ ± 100 μɛ
4.5 Conclusions
o It was possible develop a friendly and reliable user interface for data acquisition.
o The code was made in a modular manner and a storage method was established that
allows saving the data of both transducers and CAN.
o For the acceleration measurement it was possible to define the accuracy of the
equipment and instrumentation. Because the accelerometers have a measuring range
of ±4 V, it was not necessary to amplify the signal.
o For strain measurement, the minimum resolution of the NI 9206 module does not
allow a resolution lower than 1000 μɛ reading directly from the quarter bridge, so to
improve this resolution the output signal of the bridge was amplified with a ratio of
11: 1 and the resolution of the equipment became 100 μɛ.
59
Chapter 5
5 Summary and Conclusions
5.1 General Conclusion
The selected equipment demonstrated the DAQ system capability to perform
vibration and deformation measurements, as well as obtain parameters from CAN J1939
protocol at the same time with a friendly and versatile user interface developed.
The developed laboratory tests allowed to validate the repeatability and reliability of
the data defining the accuracy according to the instrumentation implemented.
5.2 Contributions
Reliability analysis of the DAQ system: The investigation of measurement
accuracy tolerances allowed to have a reference value and, through the tests, it
was possible to conclude that the system is within tolerance.
Instrumentation analysis: The investigation of signal conditioning allowed to
obtain results that are in the error limits specified in the standard.
Design of laboratory tests: To ensure the accuracy of the readings, variable control
was necessary in the tests and this was done by simulating conditions.
Laboratory tests design: To ensure the accuracy of the measurements, variable control
was necessary in the tests and this was done by simulating conditions of real tests.
60
5.3 Future Work
Implement the System in one of the different applications of the SAE J1939
communication protocol.
Take the capacity of the DAQ System from 24 to 96 channels.
Implementation of Telemetry technology to acquire data on field.
5.4 Recommendations
Knowing the range of frequency and amplitudes of the magnitudes for the analysis
is important in order to configure the parameters of the DAQ system such as
sampling frequency and input voltage range.
It is important to know the error generated by the DAQ System since, according
to the sampling frequency and the installation conditions of the sensors, such as
type and length of connection cable, this may vary and should be considered when
performing the instrumentation.
Keep in mind that the resolution of the DAQ System will give the minimum
possible measurement according to the magnitude to be measured and the type of
sensor to be implemented. According to this, it is analyzed if it is necessary to
amplify the signal.
Follow the steps described in the prototype operation manual, Annex 15.
61
References
[1] A. Gani and M. J. E. Salami, “A LabVIEW based Data Acquisition System for
Vibration Monitoring and Analysis,” pp. 3–6, 2002..
[2] R. C. Treviño, “Road Load Data Acquisition system Through Real-Time technology:
Validation and First Experiments,” Instituto Tecnológico y de Estudios Superiores de
Monterrey, 2017.
[3] R. Rajamani, “Instrumentation of Navistar Truck for Data Collection,” Department of
Mechanical Engineering, University of Minnesota, 2013.
[4] L. Alvarez, R. Henao and E. Duque, “Analog Filtering Schemes Analysis for ECG
Signals,” Universidad Tecnológica de Pereira, no. 37, pp. 103–108, 2007.
[5] S. E. Marx, “Controller Area Network (CAN) Bus J1939 Data Acquisition Methods
and Parameter Accuracy Assessment Using Nebraska Tractor Test Laboratory Data,”
2015..
[6] A. Ramirez, “Development of interface for reading and storage CAN parameters under
SAE -1939 standard,” Universidad Autónoma de Nuevo León, 2017.
[7] National Instruments, “Complete Guide to Building a Measurement System”,
[Online]. Available at:
http://download.ni.com/evaluation/daq/Measurement_System_Build_Guide.pdf
[Accessed: 10-Feb-2018].
[8] Micro Measurements, “Strain Sensor Reference Guide”, [Online]. Available at:
http://www.vishaypg.com/docs/25906/Strain-Gage-Ref-Guide.pdf [Accessed: 01-
Mar-2018].
[9] Micro Measurements, “External Bridge Completion for Strain Gage Circuits”,
[Online]. Available at: http://www.vishaypg.com/docs/11168/VMM-5.pdf [Accessed:
01-Mar-2018].
[10] Y. Lee, J. Pan, R. Hathaway, M. Barkey, “Fatigue Testing and Analysis,” Elsevier Inc,
pp. 36–37, 2005.
[11] National Instruments, “Introduction to Data Acquisition,” Data Acquisition Hardware,
2016. [Online]. Available at: http://www.ni.com/white-paper/3536/en/. [Accessed:
09-Feb-2018].
[12] The Northern Alberta Institute of Technology., Retrieved 17 October 2012.
[13] National Instruments, “Introduction to Data Acquisition,” Transducers, 2016.
[Online]. Available at: http://www.ni.com/white-paper/3536/en/. [Accessed: 09-Feb-
2018].
[14] National Instruments, “Introduction to Data Acquisition,” Signals, 2016. [Online].
Available at: http://www.ni.com/white-paper/3536/en/. [Accessed: 09-Feb-2018].
[15] National Instruments, “Introduction to Data Acquisition,” Signal Conditioning, 2016.
62
[Online]. Available at: http://www.ni.com/white-paper/3536/en/. [Accessed: 09-Feb-
2018].
[16] National Instruments, “CompactDAQ”, [Online]. Available at:
http://www.ni.com/data-acquisition/compactdaq/ [Accessed: 09-Feb-2018].
[17] National Instruments, “crio9030”, [Online]. Available at:
http://search.ni.com/nisearch/app/main/p/bot/no/ap/global/lang/en/pg/1/q/crio%2090
30/ [Accessed: 09-Feb-2018].
[18] National Instruments, “NI 9206 Datasheet”, [Online]. Available at:
http://www.ni.com/pdf/manuals/374231a_02.pdf [Accessed: 09-Feb-2018].
[19] Laboratorio Metrológico de Antioquia, NIT: 900.247.988-7, [Online]. Available at:
http://www.laboratoriometrologico.com [Accessed: 10-Feb-2018].
[20] National Instruments, “Instrument Fundamentals Complete Guide”, [Online].
Available at: http://www.ni.com/white-paper/3214/en/ [Accessed: 14-Feb-2018].
[21] OKAWA Electric, “RC Low-pass Filter Design Tool”, [Online]. Available at:
http://sim.okawa-denshi.jp/en/CRtool.php [Accessed: 14-Feb-2018].
[22] Micro Measurements, “Stress Analysis Strain Gages”, [Online]. Available at:
http://www.vishaypg.com/docs/11504/stress-analysis-selection-criteria.pdf
[Accessed: 01-Mar-2018].
[23] National Instruments, “Strain Gauge Measurement”, [Online]. Available at:
http://elektron.pol.lublin.pl/elekp/ap_notes/NI_AN078_Strain_Gauge_Meas.pdf
[Accessed: 01-Mar-2018].
63
Annexes
Annex 1
Data Acquisition System
The generalized measurement system
The simplest form of measurement system might be considered a three-phase system
which can be seen in Figure A1.1 and A1.2. The system consists of detector, which sense the
signal; a modifying stage, which typically amplifies the relatively small signal from the
sensor; and a final stage, which interprets the signal, visually displays the interpreted signal,
and provides some form of data storage.
Figure A1.1 A three-phase measurement system.
.
Detector -Transducer Stage
Modifying Stage
Indicating-Recording Stage
64
Figure A1. 2 Generalized measurement and control [10].
The detector senses desired input to the exclusion of all other inputs and provides an
analog output. The transducer is any device that accepts one form of energy from a system
and transmits that energy (typically in another form) to another system. The modifying stage
is present to modify the signal received from the transducer into an able form by the final
stage. The modifying stage commonly increases amplitude and/or power. The termination
stage provides indication and/or recording in a form for easy interpretation and evaluation.
The detector’s function is to sense input and change it to a more convenient form. Of
major interest is the transducer’s transfer efficiency. The modifying stages of interest include
amplifying, filtering, attenuating, digitizing, and other signal modification techniques. The
terminating stage is any component aiding the engineer in experimental data analysis,
including digitized indication, recorders, digitized signals for computer data analysis,
graphical displays, and possibly any controlling devices [10].
Physical variable
to be measured
INPUT STAGE
Controller
OUTPUT STAGE
Detector-
Transducer Stage
Indicating
Stage Intermediate
Stage
Recording
Data Processing
Data Storage
Calibration signal
representing a
known value of the
physical variable
External
Power
65
Data Acquisition Hardware
Data acquisition hardware acts as the interface between the computer and the outside
world. It primarily functions as a device that digitizes incoming analog signals so that the
computer can interpret them. Other data acquisition functionality includes the following:
· Analog input/output
· Digital input/output
· Counter/timers
· Multifunction - a combination of analog, digital, and counter operations on a single
device [11]
66
Annex 2
Instrumentation
Instrumentation is defined as the art and science of measurement and control of the
process variables within a production or manufacturing area [12].
Transducers
Data acquisition begins with the physical phenomenon to be measured. A transducer
is a device that converts a physical phenomenon into a measurable electrical signal, such as
voltage or current. The ability of a data acquisition system to measure different phenomena
depends on the transducers to convert the physical phenomena into signals measurable by
the data acquisition hardware. Transducers are synonymous with sensors in data acquisition
systems [13]. Is important to know that here are specific transducers for many different
applications, such as measuring temperature, pressure, or fluid flow. Table A2.1 shows a
short list of some common phenomena and the transducers used to measure them.
Table A2.1 Phenomena and Existing Transducers [13]
Phenomenon Transducer
Temperature Thermocouple, RTD, Thermistor
Light Photo Sensor
Sound Microphone
Force and Pressure Strain Gage
Piezoelectric Transducer
Position and Displacement Potentiometer, LVDT, Optical Encoder
Acceleration Accelerometer
pH pH Electrode
Different transducers have different requirements for converting phenomena into a
measurable signal. Some transducers may require excitation in the form of voltage or current.
Other transducers may require additional components and even resistive networks to produce
a signal.
67
Signals
The appropriate transducers convert physical phenomena into measurable signals.
However, different signals need to be measured in different ways. For this reason, it is
important to understand the different types of signals and their corresponding attributes.
Signals can be categorized into two groups: analog and digital [14].
Analog Signal
An analog signal can exist at any value with respect to time. A few examples of analog
signals include voltage, temperature, pressure, sound, and load. In Figure A2.1 the three
primary characteristics of an analog signal are level, shape, and frequency can be seen.
Figure A2. 1 Primary characteristics of an Analog Signal [14]
Level. - Because analog signals can take on any value, the level gives vital
information about the measured analog signal. The intensity of a light source, the
temperature in a room, and the pressure inside a chamber are all examples that
demonstrate the importance of the level of a signal. When you measure the level of a
signal, the signal generally does not change quickly with respect to time. The accuracy
of the measurement, however, is very important.
68
Shape. - Some signals are named after their specific shapes - sine, square, sawtooth,
and triangle. The shape of an analog signal can be as important as the level because
by measuring the shape of an analog signal, you can further analyze the signal,
including peak values, DC values, and slope. Signals where shape is of interest
generally change rapidly with respect to time, but system accuracy is still important.
The analysis of heartbeats, video signals, sounds, vibrations, and circuit responses are
some applications involving shape measurements.
Frequency. - All analog signals can be categorized by their frequencies. Unlike the
level or shape of the signal, you cannot directly measure frequency. You must analyze
the signal using software to determine the frequency information. This analysis is
usually done using an algorithm known as the Fourier transform.
When frequency is the most important piece of information, you need to consider
including both accuracy and acquisition speed. Although the acquisition speed for acquiring
the frequency of a signal is less than the speed required for obtaining the shape of a signal,
you still must acquire the signal fast enough that you do not lose the pertinent information
while acquiring the analog signal. The condition that stipulates this speed is known as the
Nyquist Sampling Theorem [14]. Speech analysis, telecommunication, and earthquake
analysis are some examples of common applications where the frequency of the signal must
be known.
Digital Signal
A digital signal cannot take on any value with respect to time. Instead, a digital signal
has two possible levels: high and low. Digital signals generally conform to certain
specifications that define the characteristics of the signal. They are commonly referred to as
transistor-to-transistor logic (TTL). TTL specifications indicate a digital signal to be low
when the level falls within 0 to 0.8 V, and the signal is high between 2 and 5 V. The useful
information that you can measure from a digital signal includes the state and the rate that can
been seen at Figure A2.2.
69
Figure A2. 2 Primary characteristics of a Digital Signal [14]
State. - Digital signals cannot take on any value with respect to time. The state of a
digital signal is essentially the level of the signal - on or off, high or low. Monitoring
the state of a switch - open or closed - is a common application showing the
importance of knowing the state of a digital signal.
Rate. - The rate of a digital signal defines how the digital signal changes state with
respect to time. An example of measuring the rate of a digital signal includes
determining how fast a motor shaft spins. Unlike frequency, the rate of a digital signal
measures how often a portion of a signal occurs. A software algorithm is not required
to determine the rate of a signal.
Signal Conditioning
Sometimes transducers generate signals too difficult or too dangerous to measure
directly with a data acquisition device. For instance, when dealing with high voltages, noisy
environments, extreme high and low signals, or simultaneous signal measurement, signal
conditioning is essential for an effective data acquisition system. It maximizes the accuracy
of a system, allows sensors to operate properly, and guarantees safety [15]. It is important to
select the right hardware and use signal conditioning accessories in a variety of applications
including the following:
70
Amplification
Attenuation
Isolation
Bridge completion
Simultaneous sampling
Sensor excitation
Multiplexing
71
Annex 3
Laboratory Virtual Instrument Engineering Workbench
In order to implement the DAQ system of sensors and information from the ECU’s
truck by CAN protocol, the equipment used in the theses "Road Load Data Acquisition
System Through Real-Time Technology: Validation and First Experiments" and
"Development of interface for reading and storage CAN parameters under SAE -1939
standard " were selected to, through the integration of codes, achieve one of the objectives of
this work. Following is a description of the hardware and software defined for the data
acquisition system for this project.
Hardware
CompactDAQ is a portable, rugged DAQ platform that integrates connectivity and
signal conditioning into modular I/O for directly interfacing to any sensor or signal. From in-
vehicle data logging to benchtop research, the breadth of bus, chassis, controller, and I/O
conditioning options combined with the customizable nature of LabVIEW software provide
the best solution to meet the needs of any medium-channel-count application [16].
CompactRIO
CompactRIO combines an open-embedded architecture with small size,
extreme ruggedness, and C Series modules in a platform powered by the NI
LabVIEW reconfigurable I/O (RIO) architecture.
cRIO‑9030.- is an embedded controller ideal for advanced control and
monitoring applications. This software-designed controller features an FPGA and a
real-time processor running the NI Linux Real‑Time OS. The embedded user
interface capability and Mini DisplayPort let you add a local human machine interface
(HMI) to simplify application development. This rugged, fanless controller offers an
SDHC slot and a variety of connectivity ports, including two Gigabit Ethernet, two
USB host, one USB device, and two serial [17].
72
Figure A3.1 cRIO-9030 from National Instruments
C Series Universal Analog Input Module
Provides analog input channels for voltage, current, temperature, and strain
measurements in CompactDAQ or CompactRIO systems.
C Series Universal Analog Input Modules are designed for multi-purpose
measurements, including built-in support for accelerometer, powered sensor, full-
bridge, and voltage measurements as well as quarter-bridge, half-bridge, 60 V, and
current measurements using measurement-specific adapters.
NI-9206 (C Series Voltage Input Module). - The NI 9206 C Series module for
use with any CompactDAQ or CompactRIO system features 16 differential analog
inputs, 16-bit resolution, and a maximum sampling rate of 250 kS/s. Each channel
has programmable input ranges of ±200 mV, ±1 V, ±5 V, and ±10 V [18] and can
detect a 305 μV change.
73
Figure A3.2 NI-9206 from National Instruments
C Series CAN Interface Module
Enables CompactRIO or CompactDAQ systems to connect to and
communicate on a Controller Area Network (CAN) bus.
C Series CAN Interface Modules communicate using onboard transceivers for
High-Speed/Flexible Data‑Rate or Low-Speed/Fault Tolerant CAN. C Series CAN
Interface. Using NI-XNET, applications can be created that require real-time, high-
speed manipulation of hundreds of CAN frames and signals. The NI-XNET device-
driven DMA engine enables the onboard processor to move CAN frames and signals
between the interface and the user program without CPU interrupts, minimizing
message latency and freeing host processor time. C Series CAN Interface Modules
work well in applications such as hardware-in-the-loop (HIL) simulation, rapid
control prototyping, bus monitoring, and automation control. For this application the
NI-9862 module is recommended that has a one port with high speed and flexible
data rate.
74
Figure A3.3 NI-9862 from National Instruments
Software
LabVIEW
Is systems engineering software for applications that require test,
measurement, and control with rapid access to hardware and data insights. LabVIEW
offers a graphical programming approach that helps you visualize every aspect of
your application, including hardware configuration, measurement data, and
debugging.
NI LabVIEW Real-Time Module
LabVIEW Real-Time extends the LabVIEW graphical development
environment to deliver deterministic, hard real-time performance. Use graphical
programming on your desktop PC to develop and debug applications that require
absolute reliability, extended duration run time, or stand-alone operation, and then
download the application over Ethernet to run on a variety of dedicated hardware
targets.
75
Annex 4
Method Validation
To establish the reliability of the system is necessary first to understand and apply
concepts of metrology because in our case by the type of testing is necessary to check or
calibrate equipment, for which different calibration methods derived from the established
measurement methods.
Difference between Calibrate, Verify and Adjust
These are very common terms in metrology, followed by the definition of each one
of them according to the VIM (International Vocabulary of Metrology) in the standard
JCGM200 of 2012.
Calibrate: relationship between values and their uncertainties of associated measures
obtained from the measurement patterns, and the corresponding indications with their
associated uncertainties, and establishes a relationship that allows obtaining a
measurement result from an indicator.
Verify: contribution of objective evidence that an element satisfies the specified
requirements.
Adjust: set of operations performed on a system of measure so that it provides
prescribed indications, corresponding to given values of the magnitude to be
measured.
In summary Calibrate is nothing more than comparing a standard instrument with
their associated uncertainties and a measurement instrument, Verify is nothing more than
checking that some metrological requirements are accomplished, and Adjust is not more than
make a correction to a measuring instrument to obtain exact and precise indications.
76
Traceability
The International Vocabulary of Basic and General Terms in Metrology (VIM)
defines traceability as “property of the result of a measurement or the value of a standard
whereby it can be related to stated references, usually national or international standards,
through an unbroken chain of comparisons all having stated uncertainties."
From these definitions it is deduced that to calibrate an instrument or pattern it is
necessary to have another one with more precision that provides the conventionally true value
that is the one that will be used to compare it with the indication of the instrument subjected
to calibration. The considered pattern will have been compared in turn by another pattern of
higher metrological quality until it can be related to a national pattern. This is done through
an uninterrupted and documented chain of comparisons, which is called traceability.
Prior to the calibration, a check of the instrument to be calibrated can be made and if
any type of mismatch is detected, correct it to minimize the contributions to the uncertainty.
A laboratory calibration applies to equipment that:
- The appropriate patterns are available.
- Calibration procedures or instructions and adequate technical and human
resources are available.
- The compatibility of the requirements of the measurements made with this
equipment with the results of the calibration is guaranteed.
Accuracy (from a measuring instrument)
It is the degree of approximation between the average of multiple readings and the value
conventionally accepted as a standard.
Notes:
1. The concept of accuracy is qualitative
2. The term precision must not be used for accuracy
77
Precision
Quality that characterizes the aptitude of a measuring instrument to give indications close
to the true value of the measured quantity.
Repeatability
Property of a measurement, characterized by the proximity or convergence between the
results of successive measurements of the same magnitude, carried out fulfilling the
following conditions:
* By the same observer
* With the same measurement instruments,
* In the same laboratory
* The same operating conditions of the instruments used
* Repetitions at short time intervals
* The same measurement method
Reproducibility
Property of a measurement, which includes performing them in different conditions such
as:
* Different observers
* With other measuring instruments
* In other laboratories
* In different operating conditions of the instruments used (Temperature -
Humidity - Pressure)
* At different time intervals.
* The same measurement method.
78
Table A4.1 Scheme of the concepts of accuracy, precision, repeatability and reproducibility [19]
Accuracy Inaccuracy
(Systematic Error)
Precision
Imprecision
(Low
Reproducibility)
Methods of calibration
For this project it is important to apply or develop an adequate procedure to verify the
calibration of the equipment. Then briefly described, the most common methods of
calibration, used in technical and industrial metrology.
Calibration by direct comparison
In this method, the values provided by the equipment (measurement
instrument or materialized measurement) under calibration are compared directly and
instantaneously against the values provided by a standard.
Transfer calibration
In this method, the values provided by the equipment (measurement
instrument or materialized measurement) under calibration are compared against the
values provided by a standard (reference value), through a transfer pattern, even at
different time and place.
79
Calibration by substitution
This method uses auxiliary equipment (comparator), with which the standard
is measured initially and then to the equipment (measurement instrument or
materialized measurement) subject to calibration.
Calibration by equilibrium
This method uses a null detector, which allows to check the equality between
the standard and the equipment (measurement instrument or materialized
measurement) subject of the calibration.
Calibration by simulation
This method simulates the measured or the magnitude of the measurement
instrument subject to calibration based on models of response relationship against
stimulus.
Calibration by reproduction
In this case the pattern used in the calibration reproduces the magnitude.
Calibration by fixed points
In this case the pattern used in the calibration performs a fundamental or
derivative constant by reproducing physical or chemical phenomena.
80
Annex 5
BS ISO 4866:2010.- Mechanical vibration and shock – Vibration of fixed
structures – Guidelines for the measurement of vibrations and evaluation of their
effects on structures.
This standard indicates that the measurement of the vibration in a structure is carried
out for different purposes:
a) problem recognition, where it is reported that a structure is vibrating at such a level
as to cause concern to occupants and equipment, possibly making it necessary to
establish whether the levels warrant concern for structural integrity;
b) control monitoring, where maximum permitted vibration levels have been
established by an agency and those vibrations have to be measured and reported;
c) documentation, where dynamic loading has been recognized in design, and
measurements are made to verify the predictions of response and provide new design
parameters;
d) diagnosis, where it has been established that vibration levels require further
investigation, measurements are made in order to provide information for mitigation
procedures.
About frequency range of interest, this standard describes that it depends upon the
spectral content of the excitation and upon the mechanical response of the structure. Most
structural damage from man-made sources occurs in the frequency range from 1 Hz to 150
Hz.
The Instrumentation must have a continuous measurement of vibration amplitude to
characterize the vibration. The measurement shall be recorded over a sufficiently long time,
and taken with sufficient accuracy to extract its spectral content.
For the applications dealt with in this International Standard, two main classes of
measurement are considered:
a) class 1 for engineering analysis;
b) class 2 for field monitoring.
81
It is important to highlight class 2 that is related to the current project. This category
of instrumentation is used for vibration control after definition of major parameters by
engineering analysis or to monitor known vibration phenomena. The frequency and
amplitude characteristics are determined by the results obtained by the engineering analysis.
According to the Source of vibration, there are defined ranges of frequency,
amplitude, speed and acceleration that should be considered at the moment of performing the
instrumentation. In the table A5.1, parameters considered by this standard are presented.
Table A5.1 Range of structural response for various sources.
IS ISO 13373 – 2:2005.- Condition monitoring and diagnostics of machines –
Vibration condition monitoring – Part 2 Processing, analysis and presentation of
vibration data.
This standard specifies that, virtually, all vibration measurements are obtained using
a transducer that produces an analog electrical signal that is proportional to the instantaneous
value of the vibratory acceleration, velocity or displacement. The signal can be recorded on
82
a dynamic system analyzer, investigated for later analysis or displayed, for example, on an
oscilloscope. To obtain the actual vibration magnitudes, the output voltage is multiplied by
a calibration factor that accounts for the transducer sensitivity and the amplifier and recorder
gains.
Another important topic that describes the standard is the concept of aliasing, which
is a false representation of a frequency that can result when the sampling rate of a digital
analyzer is too low to describe that frequency adequately. This effect is eliminated by low-
pass filtering the signal before sampling to ensure that it does not contain frequency
components above half the sampling frequency. When the sampling rate is set exactly at two
times the maximum expected frequency, this is known as the Nyquist frequency. In practice,
most sampling rates are set at greater than two times the maximum frequency (about 2,56
times) to allow for a low-pass filter without a sharp cut-off.
Figure A5. 1 Aliasing - Inaccurate waveform representation [20].
IS ISO 8041 - 2005.- Human response to vibration – Measuring instrumentation.
This International Standard specifies the performance specifications and tolerance
limits for instruments designed to measure vibration values, for the purpose of assessing
human response to vibration. The table A5.2 presents the reference parameters according to
the application.
83
Table A5.2 Reference vibration values and frequencies.
Application Nominal Frequency
Range Hz
Reference
Frequency r.m.s. Acceleration
Value m/s2
Hand transmitted 8 to 1000 500 rad/s (79.58 Hz) 10
Whole body 0.5 to 80 100 rad/s (15.915 Hz) 1
Low frequency 0.1 to 0.5 2.5 rad/s (0.397 Hz) 0.1
The standard also indicates that there are tolerances and separates the errors of the
signal acquisition equipment from those of the measurement made with the selected
instrumentation, table A5.3 presents the reference tolerances described above.
Table A5.3 Tolerances of indication at reference frequency and vibration value.
Parameter Tolerance
Tolerance of the electrical part of the instrument ± 2 %
Tolerance of the vibration transducer response ± 3 %
Tolerance of indication at the reference frequency
under reference environmental conditions ± 5 %
The error ɛ of the test measurement atest is expressed as a percentage of the reference
vibration transducer measurement aref.
ɛ =𝒂𝒕𝒆𝒔𝒕− 𝒂𝒓𝒆𝒇
𝒂𝒓𝒆𝒇× 𝟏𝟎𝟎% (A5 1)
It should be noted that this standard delivers the specifications of the transducer
according to the type of application. The next table presents the specifications of the
transducer applied in vehicles for whole body.
84
Table A5.4 Vibration transducer specifications.
Characteristic Measurement issue Influence on
measurement uncertainty
Whole-hody
vibration
Vehicles
Maximum total mass (of
all vibration transducers
and mounting system)
< 10 % of the effective mass of the vibrating
structure
450 g on seat,
50 g elsewhere
Maximum vibration
transducer mass 50 g
Maximum total size (of all
vibration transducers and
mounting system)
Unobtrusive, minimum interference with
normal activities.
On seat:
300 mm diameter
x 12 mm height
Other locations:
30 mm cube
Maximum mounting
height
Where a vibration transducer is mounted
above a vibrating surface (e.g. on a mounting
block) but is aligned, measure the vibration
parallel to that surface. Then the distance
between the measurement axis of the vibration
transducer and the mounting surface should be
as small as possible. This will minimize the
amphfication of rotational acceleration
components.
10 mm
Temperature range -10 °C to 50 °C
Transverse sensitivity < 5%
Maximum unweighted
shock acceleration
The vibration transducer needs to be capable
of withstanding the high unweighted shock
accelerations to which it may be exposed,
while providing accurate information within
the measurement frequency range.
1000 m/s2
Minimum resonant
frequency
Should be greater than approximately 10
times the nominal upper frequency limit. 800 Hz
85
IS ISO 16063 – Methods for the calibration of vibration and shock transducers
The ISO 16063 series of standards is concerned with methods for the calibration of
vibration and shock transducers under both standard laboratory conditions and in the field.
Part 11.- Primary vibration calibration by laser interferometry
Uncertainty of measurement. - The limits of the uncertainty of measurement
applicable to this part of ISO 16063 shall be as follows.
a) For the magnitude of sensitivity:
0,5 % of the measured value at reference conditions;
≤ 1 % of the measured value outside reference conditions
b) For the phase shift of sensitivity:
0,5° of the measured value at reference conditions;
≤ 1° of the reading outside reference conditions.
Recommended reference conditions are as follows:
- frequency in hertz: 160, 80, 40, 16 or 8 (or radian frequency ω = 1 000, 500, 250,
100 or 50 radians per second);
- acceleration in meters per second squared (acceleration amplitude or r.m.s. value):
100, 50, 20, 10, 5, 2 or 1.
Part 21.- Vibration calibration by comparison to a reference transducer
This part of ISO 16063 specifies procedures for performing calibrations of rectilinear
vibration transducers by comparison in the frequency range from 0,4 Hz to 10 kHz. Below is
a diagram of the measurement system to perform calibration by comparison to a reference
transducer.
86
Key
3 Signal generator 3 Shaker 5 Prototype
4 Amplifier 4 Filter 6 Pattern equipment
7 Reference transducer
Figure A5. 2 Measuring system for vibration validation by comparison to a reference transducer
87
Annex 6
Virtual session in LabVIEW to interact with the NI 9862 module
To start the virtual session, right click on the CRIO, then New and finally on the NI-
XNET Session. The following figure illustrates the specified route.
Figure A6. 1 Virtual Session NI-XNET
In the pop-up window, you configure the Frame Inputs in a Stream mode as shown in
the following figure.
88
Figure A6. 2 Virtual Session NI-XNET.- Enter Mode: Stream Frame Input
If a correct communication with the module is established, a new pop-up window will
be presented to configure the Hardware and Cluster selection. At the first tab a name will be
assigned to the session and the interface that has the enabled port will be selected. If an
interface is not displayed, there is a problem with the connection. At the Cluster selection tab
in Database, select the NIXNET_example option and Cluster J1939_Over_CAN.
Figure A6.3 and A6.4 shows the user interface generated with the code for the
integration tests. The sampling frequency and sensor type is configured at the Sensor
Definition tab, while the parameters to be decoded from the CAN frame are determined at
CAN tab.
89
Figure A6. 3 User Interface Integration Tests. - Data and Sensor Configuration
Figure A6. 4 User Interface Integration Tests. - CAN Configuration
Once the parameters are established, the program is run and the channel reading can
be visualized as well as the CAN parameters inside the test frame, this can be seen in Figures
A6.5 and A6.6.
90
Figure A6. 5 User Interface for Data Collection Integration Tests
Figure A6. 6 User Interface for Data Collection Integration Tests
91
Annex 7
Code and User Interface Develop
The first tab allows entering general parameters of the test such as the type of truck, the driver
and the technician in charge of the test, this can be seen in Figure A7.1.
The next tab corresponds to the configuration of the analog signals, the sampling
frequency and the name of the file to be generated at the end of the test. For the configuration
of analog signals, the type of measurement to be performed, whether this is acceleration or
deformation, can be selected. The software with this information will perform the respective
conversion, or you can simply select another one and take the direct reading in volts. In
addition, the developed code allows selecting a calibration of the channel, which is explained
in detail later. Figure A7.2 shows the parts described in this part.
Figure A7. 1 User Interface. - General information
92
Figure A7. 2 User Interface. – Transducer selection, sampling frequency and file name configuration.
The third and fourth tab show the readings and graphs of the selected transducers after
running the program, this as a visual aid for the technician in charge since these data are
stored in a .tdms format file at the end of the tests for later analysis.
Figure A7. 3 User Interface. – Measurement Reading.
93
Figure A7. 4 User Interface. – Measurement Plot.
Finally, the CAN parameters to be decoded are selected and graphs of the data
collected during the test can be displayed in real time. This data is stored in the same .tdms
file together with the data of the selected sensors.
Figure A7. 5 User Interface. – CAN Parameters.
94
For the development of the entire code, a main VI was established with the help of
additional Sub VIs to carry out the modular implementation of readings for each channel.
Figure A7. 6 VIs used for programming.
Figure A7.6 shows the VIs implemented, then a description of each of them:
DAQ System Principal. - It is the main VI and contains the code for the acquisition
of analog signals as well as CAN parameters which are stored in a USB drive.
Units Conversion. - It allows taking the readings of the channel and transforms them
into g units for accelerometers and micro deformation for strain gages or direct
measurement in volts if another is selected.
Units. - It allows to concatenate information from the sensor in order to generate the
header of the column of the stored data.
Variable Reset. - At the end of each test, it allows to reset the channel configuration
for the entry of new parameters, otherwise the data of the last test will be maintained.
Reset All Sensors. - Allows at the end of each test to reset all parameters in all
channels.
The following figure allows to visualize the code to acquire analog signals in a
modular way, that is, is possible to copy this block and replicate it as many channels is
95
needed, changing the variable according to the channel number to be assigned in NI 9206
modules. The numbers that are entered into the sub VI Units must be updated so that, when
saving the header information, they correspond to the designated channel.
.
Figure A7. 7 Data acquisition code. - Modular block.
On the other hand, during the tests to reduce the error in the measurements, a
calibration algorithm was developed, which takes 5000 samples corresponding to 6.25
seconds with a rate of 800 samples per second. With this number of samples, the average
value is calculated, which will be used to correct the offset that may occur at the time of
measurements with the different transducers. This is optional since correcting the offset could
be done manually if the technician in charge so wishes.
Figure A7. 8 Data acquisition code. - Calibration block.
When you press the Stop button, the test ends, the .tdms file is written or closed according
to the selected storage method and finally the generated file is stored in a USB memory.
96
Annex 8
Data Storage Methods
In the first method, all the readings are stored in one in an array that, after
completing the test, is called to write the information in the .tdms file. which will be
recorded on the USB drive. Parts of the code generated for this method can be visualized in
figures A8.1 and A8.2.
Figure A8.1 Measures are stored in independent array variables.
97
Figure A8.2 Method 1.- All variables are written at the end of the test.
Method 2 while the measurements are taken, these are written in the .tdms file and
once the test is finished, the file is closed and stored in a USB drive.
98
Figure A8.3 Method 2.- Measures are stored in one array variable.
.
99
Figure A8.4 Method 2.- Variable is written at the entered sampling frequency.
It should be mentioned that in the first method the sampling frequency depends on
the period between each measurement and keeping in mind that the sampling frequency of
the CAN parameters differs, at the time of generating the .tdms file there would be gaps in
the columns of these parameters and this information could not be related to the readings of
the transducers. For this reason the second method was selected since the sampling frequency
depends on the time period for writing in the .tdms file, which allows to relate the
measurement of the transducers with the last reading of each selected parameter of the CAN
module.
100
Annex 9
MEMS accelerometers by manufacturer
Transducer Brands
Transducer Model Range
(g) Sensitivity
(mV/g) Hz frequency range (3dB)
Input
Dytran 7500A7 200 10 0 to 2500 9 to 32 V
Dytran 7500A6 100 20 0 to 2500 9 to 32 V
Endevco 7290A-30 30 66 ±4 0 to 800 9.5 to 18V
Endevco 7290A-100 100 20 ±1 0 to 1000 9.5 to 18V
Kistler 8310A50M11SP1M 50 40 0 to 500 3,8 ... 16V
Kistler 8310A25A1 25 80 0 to 300 3,8 ... 16V
PCB 3741D4B100G 100 20 0 to 1000 6 to 30 V
PCB 3741B12100G 100 20 0.5 to 100 6 to 30 V
Silicon Design 2260-400 400 10 0 – 2000 14 to 32 V
Silicon Design 2240-400 400 10 0 – 2000 13 to 32 V
Silicon Design 2220-200 200 20 0 – 1750 11 to 32 V
Silicon Design 2220-100 100 40 0 – 1400 12 to 32 V
Silicon Design 2210-400 400 10 0 – 2000 8 to 32 V
Silicon Design 2210-200 200 20 0 – 1750 10 to 32 V
Silicon Design 2210-100 100 40 0 – 1400 9 to 32 V
Table A9.1 Models of MEMS accelerometers by manufacturer.
101
Annex 10
Error Estimation for Acceleration Test
For this application, the voltage range defined is ± 5 V and the equations for the
calculation of absolute accuracy for NI 92016 module are presented below.
𝑨𝒃𝒔𝒐𝒍𝒖𝒕𝒆 𝑨𝒄𝒄𝒖𝒓𝒂𝒄𝒚 = 𝑹𝒆𝒂𝒅𝒊𝒏𝒈 ∗ 𝑮𝒂𝒊𝒏 𝑬𝒓𝒓𝒐𝒓 + 𝑹𝒂𝒏𝒈𝒆 ∗ 𝑶𝒇𝒇𝒔𝒆𝒕 𝑬𝒓𝒓𝒐𝒓 +
𝑵𝒐𝒊𝒔𝒆 𝑼𝒏𝒄𝒆𝒓𝒕𝒂𝒊𝒏𝒕𝒚 (A10 1)
𝑮𝒂𝒊𝒏 𝑬𝒓𝒓𝒐𝒓 = 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍 𝑮𝒂𝒊𝒏 𝑬𝒓𝒓𝒐𝒓 + 𝑮𝒂𝒊𝒏 𝑻𝒆𝒎𝒑𝒄𝒐 ∗
𝑻𝒆𝒎𝒑 𝑪𝒉𝒂𝒏𝒈𝒆 𝒇𝒓𝒐𝒎 𝑳𝒂𝒔𝒕 𝑰𝒏𝒕𝒆𝒓𝒏𝒂𝒍 𝑪𝒂𝒍 𝑹𝒆𝒂𝒅𝒊𝒏𝒈 ∗ 𝑮𝒂𝒊𝒏 𝑬𝒓𝒓𝒐𝒓 + 𝑹𝒂𝒏𝒈𝒆 ∗ 𝑶𝒇𝒇𝒔𝒆𝒕 𝑬𝒓𝒓𝒐𝒓 +
𝑵𝒐𝒊𝒔𝒆 𝑼𝒏𝒄𝒆𝒓𝒕𝒂𝒊𝒏𝒕𝒚 (A10 2)
𝑶𝒇𝒇𝒔𝒆𝒕 𝑬𝒓𝒓𝒐𝒓 = 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍 𝑶𝒇𝒇𝒔𝒆𝒕 𝑬𝒓𝒓𝒐𝒓 + 𝑶𝒇𝒇𝒔𝒆𝒕 𝑻𝒆𝒎𝒑𝒄𝒐 ∗
𝑻𝒆𝒎𝒑 𝑪𝒉𝒂𝒏𝒈𝒆 𝒇𝒓𝒐𝒎 𝑳𝒂𝒔𝒕 𝑰𝒏𝒕𝒆𝒓𝒏𝒂𝒍 𝑪𝒂𝒍 𝑹𝒆𝒂𝒅𝒊𝒏𝒈 + 𝑰𝑵𝑳 𝑬𝒓𝒓𝒐𝒓 (A10 3)
𝑵𝒐𝒊𝒔𝒆 𝑼𝒏𝒄𝒆𝒓𝒕𝒂𝒊𝒏𝒕𝒚 =𝑹𝒂𝒏𝒅𝒐𝒎 𝑵𝒐𝒊𝒔𝒆∗𝟑
√𝟏𝟎𝟎 𝒇𝒐𝒓 𝒂 𝒄𝒐𝒗𝒆𝒓𝒂𝒈𝒆 𝒇𝒂𝒄𝒕𝒐𝒓 𝒐𝒇 𝟑 𝝈 𝒂𝒏𝒅 𝒂𝒗𝒆𝒓𝒂𝒈𝒊𝒏𝒈 𝟏𝟎𝟎 𝒑𝒐𝒊𝒏𝒕𝒔
(A10 4)
For these equations, the manufacturer also presents the values that the different
variables take according to the chosen measurement range. The following table shows the
values of the variables that correspond to the range of ± 5 V.
Table A10.1 Variable Values for Accuracy Calculation
Variable Value
Residual gain error 135 ppm of Reading
Gain Tempco 11 ppm/°C
Reference Tempco 5
Residual Offset error 20 ppm of range
Offset tempco 47 ppm of range/°C
INL error 76 ppm of range
102
The result of the accuracy at a scale of ± 5V is presented below:
Table A10.2 Accuracy for NI 9206 at ±5V Scale.
Accuracy at ±5 V Scale Random Noise, σ Sensitivity2
±3,230 Μv 116 μVrms 46.6 μV
This accuracy is important to relate to the measurement range of the accelerometer.
It is known, by manufacturer's specification, that the output range of the selected
accelerometer 2220-100 with differentiated connection is ± 4V and the measurement range
is ± 100 g, which gives us that for every g we have 0.04 V or 40 mV.
In this case the sensitivity of the sensor series 23246 given by the manufacturer is
40.15 mV / g. Considering the accuracy of the NI 9206 module of ± 3.23 mV, the accuracy
in the measurement with the accelerometers would be ± 0.08 g. Keeping this in mind for
measurements below 1.5 g the error could be greater than 5%, however for measurements
greater than 1.5 g the error would be below 5%, this can be seen better in Figure A10.1.
Figure A10. 1 Theoretical error related to the level of g of the measurement.
103
For the test, the reference value will be 1V at the output of the signal generator and
the shaker will be started. Three tests will be performed for each frequency established within
the range of analysis. From each file test, using the Microsoft Excel as a calculation tool, the
RMS is established to determine the amplitude of the prototype and pattern readings, then
the equation A5 1 (Annex 5) is applied to calculate the error of the measurement.
On the other hand, for the sampling frequency of analysis from 0 to 80 Hz it is
important to define the sampling frequency to avoid the Aliasing, for this the Nyquist
Theorem is applied. Keeping on mind that the normative indicates that the error in the
measurement should not be greater than 5%, National Instruments in its instrumentation
fundamentals guide [20] is considered the calculation of the error in the amplitude whose
equation is presented next.
𝑨𝒎𝒑𝒍𝒊𝒕𝒖𝒅𝒆 𝑬𝒓𝒓𝒐𝒓 = 𝟏𝟎𝟎 ( 𝟏 − 𝑹
√𝟏+𝑹𝟐) , 𝒘𝒉𝒆𝒓𝒆 𝑹 =
𝑩𝑾
𝑭𝒊𝒏 (A10 5)
The amplitude error is expressed as a percentage, and R is the ratio of the
oscilloscope’s bandwidth to the input signal frequency (Fin).
If our prototype has a bandwidth of 80 Hz with an 80 Hz and sine wave input signal
at 1 V (BW = 80 Hz and Fin = 80 Hz), this means R = 1. Then using Equation A10 5 the
amplitude error would be as follows:
𝑨𝒎𝒑𝒍𝒊𝒕𝒖𝒅𝒆 𝑬𝒓𝒓𝒐𝒓 = 𝟏𝟎𝟎 ( 𝟏 − 𝟏
√𝟐) ≈ 𝟐𝟗. 𝟑 %
The calculated amplitude error would be 29.3% which is out of the limit. In practice
it is recommended to have a sampling frequency 10 times higher than the analysis frequency
range, in our case it would be 800 Hz. Considering this we would have a device with a
bandwidth of 400 Hz according to the Nyquist theorem and 80 Hz sine wave signal, this
means R = 5. Using the equation A10 5 the amplitude error would be:
104
𝑨𝒎𝒑𝒍𝒊𝒕𝒖𝒅𝒆 𝑬𝒓𝒓𝒐𝒓 = 𝟏𝟎𝟎 ( 𝟏 − 𝟓
√𝟏 + 𝟓𝟐) ≈ 𝟐 %
The amplitude error generated with a sampling rate of 800 Hz, which would allow
analysis in the range of 0 to 400 Hz by the Nyquist theorem, and a frequency of 80 Hz would
be approximately 2%.
To avoid the aliasing of the analog signal, a low pass RC filter Butterworth will be
applied, this is shown in Figure 10.2. To identify which components to use, the Bode diagram
calculator tool from OKAWA Electric [21] was used to calculate a low pass RC filter and
thus know the voltage loss in dBV, for this will be considered the following equation.
𝑽𝒐𝒍𝒕𝒂𝒈𝒆 𝑳𝒆𝒗𝒆𝒍 𝑳𝑽 = 𝟐𝟎 𝑳𝒐𝒈𝟏𝟎 (𝑽
𝑽𝒐) 𝒅𝑩𝑽 (A10 6)
Figure A10. 2 RC Low Pass Filter.
Keeping in mind that the maximum permissible error is 5%, if we take as reference
an Input Voltage of 1 V, at the output the voltage should be 0.95 V at 80 Hz. equation
A10 6 is applied to know the allowed loss in dBV .
𝑽𝒐𝒍𝒕𝒂𝒈𝒆 𝑳𝒆𝒗𝒆𝒍 𝑳𝑽 = 𝟐𝟎 𝑳𝒐𝒈𝟏𝟎 (𝟎. 𝟗𝟓
𝟏) 𝒅𝑩𝑽 = −𝟎. 𝟒𝟓 𝒅𝑩𝑽
Several values of commercial components were entered, both for resistors and
capacitors, and it was considered to use a resistance of 47 Ohms and a capacitor of 10 μF.
The filter with these components have a cut-off frequency of 338 Hz. Below is the Bode
105
diagram in which can be verified that the voltage level is attenuated in -3dB when it reaches
a frequency of 338 Hz approximately.
Figure A10. 3 Bode diagram since 10 Hz to 1000 Hz – Fc = 338 Hz.
Since the frequency of analysis will be from 0 to 80 Hz, the previous Bode diagram
will be analyzed in the range of 10 to 100 Hz. This diagram is presented in figure A10.4 and
it can be seen that in this range the voltage drop is less than -0.22 dBV which then considering
a 1V input signal and applying equation A10 6 a voltage of 9.75 is obtained 0.975 which
gives an error of - 2.5%.
Figure A10. 4 Bode diagram since 10 Hz to 100 Hz - Lv = -0.22 dBV.
Finally, the error in the measurement with the accelerometer according to the
manufacturer's specifications is typically 1% and can reach 2% maximum.
338 Hz
106
Annex 11
Measurement Analysis for Acceleration Test
The following table presents a summary of the measurements taken. It should be
noted that to evaluate the behavior of the applied filter, the difference voltage in voltage at
500 Hz in the Bode diagram was revised and this value being approximately -4.5 dBV. Then,
equation A10 6 (Annex 10) was applied to find how much voltage is obtained at the output
witth voltage input of 1 V and the value was 0.5956 V which represents an error of -40%
approximately. This value is included at the end of the following table with the estimated
theoretical error values that served as a reference.
Table A11. 1 Comparative Real vs Theoretical Error.
Frequency (Hz)
G 23246 NI Prototype (g)
G 23246 B&K Pattern (g)
Difference (g)
Error (%)
Estimate Error (%)
0.4 0.6 0.68 -0.08 -12 > 10
5 0.61 0.69 -0.08 -12 > 10
10 0.81 0.87 -0.06 -7 > 10
20 1.43 1.47 -0.04 -3 7 to 10
30 2.24 2.28 -0.04 -2 3 to 5
40 3.14 3.15 -0.01 0 < 3
50 3.94 4.01 -0.07 -2 < 3
60 4.84 4.95 -0.11 -2 < 3
70 5.61 5.77 -0.16 -3 < 3
80 6.1 6.32 -0.22 -3 < 3
500 2.99 4.81 -1.82 -38 -40%
Remind that the minimum measurement would be 0.08 g, in order not to induce false
measurements, it will be established that the prototype for this application will have a
resolution of 0.1 g and with this, the uncertainty will be estimated. The following table
presents a new error calculation keeping in mind the resolution of a tenth of g.
107
Table A11.2 Resolution 0.1 g - Real vs Theoretical Error.
Frequency (Hz)
G 23246 NI (g)
G 23246 B&K (g)
Difference (g)
Error (%)
Estimate Error (%)
0.4 0.6 0.7 -0.1 -14% > 10
5 0.6 0.7 -0.1 -14% > 10
10 0.8 0.9 -0.1 -11% > 10
20 1.4 1.5 -0.1 -7% 7 to 10
30 2.2 2.3 -0.1 -4% 3 to 5
40 3.1 3.2 -0.1 -3% < 3
50 3.9 4 -0.1 -3% < 3
60 4.8 5 -0.2 -4% < 3
70 5.6 5.8 -0.2 -3% < 3
80 6.1 6.3 -0.2 -3% < 3
500 3 4.8 -1.8 -38% -40%
As the frequency increases above 10 Hz, so does acceleration and exceeds 1 g,
evidencing that the error falls below 5%, thus remaining within the analysis range. Above 80
Hz, the low pass filter starts to work and already at 500 Hz it reduces the signal by 38%.
108
Annex 12
Error Estimation for Strain Test
To perform the measurement with strain gage, a Wheatstone bridge was used to detect
a voltage change with the variation of one of the resistors that are part of the bridge.
Figure A12. 1 Quarter-Bridge Circuit.
From the previous circuit after solving the meshes the following equation can be
obtained:
𝑽𝒐 = (𝑹𝟐
𝑹𝟏+𝑹𝟐−
𝑹𝟑
𝑹𝟑+𝑹𝟒) 𝑽𝑬𝑿 (A12 1)
Where Vo is the voltage measured while VEX is the power source of the circuit. If
R1 = R3 = R4 = R, the above equation would be a function of the resistors R2 and R as well
as the voltage of the source.
𝑽𝑶 = (𝑹𝟐
𝑹+𝑹𝟐−
𝟏
𝟐) 𝑽𝑬𝑿 (A12 2)
From the Stress Analysis Strain Gages Manual [22] it should be considered that the
Gage Factor (GF) is the measure of sensitivity, or output, produced by a resistance strain
gage. Gage factor is determined through calibration of the specific gage type, and is the ratio
between ΔR / Ro and ΔL / L (strain), where Ro is the initial unstrained resistance of the gage.
109
𝑮𝑭 =∆𝑹
𝑹∆𝑳
𝑳
=∆𝑹
𝑹
𝜺 (A12 3)
Each gage package is supplied with the GF as well as its tolerance and temperature
sensitivity. In the case of the selected 350 Ω strain gage, it has a range of 5% of strain (ɛ) and
the value of GF = 2.155. With these value, ∆ R can be calculated.
∆𝑹 = 𝜺𝑮𝑭𝑹 = 𝟎. 𝟎𝟓 ∗ 𝟐. 𝟏𝟓𝟓 ∗ 𝟑𝟓𝟎 = 𝟑𝟕. 𝟕 Ω (A12 4)
The above gives us a range of variable resistance, however in the Strain Gauge
Measurement tutorial [23], the relationship between the input voltage Vex and the voltage
Vo is given by the following equation.
𝑽𝑶
𝑽𝑬𝑿= −
𝑮𝑭∗𝜺
𝟒(
𝟏
𝟏+𝑮𝑭∗𝜺
𝟐
) (A12 5)
From the above equation, the strain (ɛ) can be calculated with the following equation.:
𝜺 = −𝟒 𝑽𝒐
𝑮𝑭(𝑽𝑬𝑿+𝟐𝑽𝑶) (A12 6)
If it is known that by implementing a voltage regulator we can obtain Vo = 5 ± 0.1V,
the minimum reading with NI 9206 of ± 3.23 mV and gauge factor GF = 2.155 were
considered to calculate the estimated error, the values are shown in the following table.
Table A12.1 Strain Error Estimation
VEX (V) VO (V) GF Strain Strain (μɛ) Resolution(μɛ) Theoretical
Error
4.9 0.00323 2.155 -0.12% -1222 -1000 -18%
5 0.00323 2.155 -0.12% -1198 -1000 -16%
5.1 0.00323 2.155 -0.12% -1174 -1000 -15%
4.9 -0.00323 2.155 0.12% 1225 1000 -18%
5 -0.00323 2.155 0.12% 1201 1000 -17%
5.1 -0.00323 2.155 0.12% 1177 1000 -15%
110
Using the Crocodrile Clips circuit simulator, the measurement circuit was designed,
see Figure A12.2, with the Wheatstone bridge and as 1 Ohm is varied, a variation of 3.57 mV
is obtained, which is very close to the resolution of the equipment.
Figure A12. 2 Voltage Measurement Simulation with Quarter-Bridge Circuit.
If within the range of variation of resistance, this is modified at the rate of 1 Ohm,
the behavior of the theoretical error can be seen in the following graph.
Figure A12. 3 Theoretical Strain Error Behavior.
From the previous graph the error can be grouped into ranges according to the
strain.
111
Annex 13
Measurement Analysis for Strain Test
This measurement was made visually and compared with the reading of the pattern
equipment.
a.-
b.-
Figure A13. 1 a.- Channel 13 % Strain Level b.- Channels 1 and 2 Voltage Measurements.
112
Figure A13.1a shows reading of channel 13 with approximately - 2% strain, which in
Voltage is approximately 55 mV according to the readings of channels 1 and 2, see Figure
A13.1b. An analysis of the readings taken with channel 13 are presented in the following
table.
Table A13. 1 Prototype Error for Strain Measurement – Channel 13.
Multimeter
MUL-280 B&K 3160-A Prototype without Calibration
VEX (V)
GF Vo
(mV) Strain
Vo (mV)
Strain Strain
Channel 13
Error Mult
Error B&K
5.07 2.155 136.1 -4.73% 137 -4.76% -4.8% 1.48% 0.84%
5.07 2.155 109.1 -3.83% 109 -3.83% -3.6% -6.01% -6.01%
5.07 2.155 82.6 -2.93% 83 -2.94% -3.0% 2.39% 2.04%
5.07 2.155 54.8 -1.96% 55.5 -1.99% -2.0% 2.04% 0.50%
5.07 2.155 32.6 -1.18% 32.8 -1.19% -1.2% 1.69% 0.84%
5.07 2.155 -6.0 0.22% -5.25 0.19% 0.2% -9.09% 5.26%
5.07 2.155 -26.6 0.98% -26.8 0.99% 1.0% 2.04% 1.01%
5.07 2.155 -52.6 1.97% -53.5 2.00% 2.1% 6.60% 5.00%
5.07 2.155 -78.8 2.98% -79.75 3.02% 3.1% 4.03% 2.65%
5.07 2.155 -109.1 4.17% -110 4.21% 4.3% 3.12% 2.14%
5.07 2.155 -133.5 5.16% -134.5 5.20% 5.2% 0.78% 0.00%
The calculated error is presented in Figure A13.2 for which strain greater than 1%
have an error that is around ± 6% while for strain less than 1% the error is greater than -8%.
113
Figure A13. 2 Error related to level of Strain Measurement – Channel 13.
The next analysis considers the measurements without calibration (Channel 1) and,
using equation A12 6 (Annex 12), the strain value is calculated. The data are presented in the
following table.
Table A13. 2 Prototype Error for Strain Measurement – Channel 1
Multimeter
MUL-280 B&K 3160-A Prototype without Calibration
VEX (V)
GF Vo
(mV) Strain
Vo (mV)
Strain Vo (mV)
Channel 1 Strain Error Mult Error B&K
5.07 2.155 136.1 -4.73% 137 -4.76% 137.5 -4.78% 1.06% 0.42%
5.07 2.155 109.1 -3.83% 109 -3.83% 110 -3.86% 0.78% 0.78%
5.07 2.155 82.6 -2.93% 83 -2.94% 82.5 -2.93% 0.00% -0.34%
5.07 2.155 54.8 -1.96% 55.5 -1.99% 55 -1.97% 0.51% -1.01%
5.07 2.155 32.6 -1.18% 32.8 -1.19% 32.5 -1.18% 0.00% -0.84%
5.07 2.155 -6 0.22% -5.25 0.19% -5 0.18% -18.18% -5.26%
5.07 2.155 -26.6 0.98% -26.8 0.99% -27.5 1.02% 4.08% 3.03%
5.07 2.155 -52.6 1.97% -53.5 2.00% -53 1.98% 0.51% -1.00%
5.07 2.155 -78.8 2.98% -79.75 3.02% -80 3.02% 1.34% 0.00%
5.07 2.155 -109.1 4.17% -110 4.21% -110 4.21% 0.96% 0.00%
5.07 2.155 -133.5 5.16% -134.5 5.20% -135 5.22% 1.16% 0.38%
114
Figure A13. 3 Error related to level of Strain Measurement – Channel 1
In the previous graph you can see that error is reduced, this is because the reading
was made directly in mV and then the conversion was made knowing the power voltage that
was 5.07 V. The code has a constant value of 5V as power of the bridge, so the variation of
the error must be analyzed by the accuracy given by the manufacturer of the voltage regulator
LM 7805 of ± 0.1 V, this is shown in tables A13.3 and A13.4.
Table A13. 3 Difference of error by accuracy bridge power supply 5.1 V
Prototype without Calibration
Strain VEX 5V Strain VEX 5.1V Difference Error Voltage Source
-4.8% -4.7% -0.1% 2.1%
-3.9% -3.8% -0.1% 2.6%
-3.0% -2.9% -0.1% 3.4%
-2.0% -2.0% 0.0% 0.0%
-1.2% -1.2% 0.0% 0.0%
0.2% 0.2% 0.0% 0.0%
1.0% 1.0% 0.0% 0.0%
2.0% 2.0% 0.0% 0.0%
3.1% 3.0% 0.1% 3.3%
4.3% 4.2% 0.1% 2.4%
5.3% 5.2% 0.1% 1.9%
115
Table A13. 4 Difference of error by accuracy bridge power supply 4.9 V
Prototype without Calibration
Strain VEX 5V Strain VEX 4.9V Difference Error Voltage Source
-4.8% -4.9% 0.1% -2.0%
-3.9% -4.0% 0.1% -2.5%
-3.0% -3.0% 0.0% 0.0%
-2.0% -2.0% 0.0% 0.0%
-1.2% -1.2% 0.0% 0.0%
0.2% 0.2% 0.0% 0.0%
1.0% 1.1% -0.1% -9.1%
2.0% 2.1% -0.1% -4.8%
3.1% 3.1% 0.0% 0.0%
4.3% 4.4% -0.1% -2.3%
5.3% 5.4% -0.1% -1.9%
Remind that the minimum measurement would be 0.11 % of strain, in order not to
induce false measurements, it will be established that the prototype for this application will
have a resolution of 0.1 % and with this, the uncertainty will be estimated. The following
table presents a new error calculation keeping in mind the resolution of a tenth of strain
percentage.
Table A13. 5 Resolution 0.1 % of Strain .- Real vs Theoretical Error.
NI (%) Multimeter MUL-280 (%ɛ)
Difference 1 (%ɛ)
Error 1 (%)
B&K 3160-A (%ɛ)
Difference 2 (%ɛ)
Error 2 (%)
Estimate Error (%)
-4.8% -4.8% 0.0% 0.0% -4.8% 0.0% 0.0% < 5
-3.9% -3.9% 0.0% 0.0% -3.9% 0.0% 0.0% < 5
-3.0% -3.0% 0.0% 0.0% -3.0% 0.0% 0.0% < 5
-2.0% -2.0% 0.0% 0.0% -2.0% 0.0% 0.0% 5 to 10
-1.2% -1.2% 0.0% 0.0% -1.2% 0.0% 0.0% 5 to 10
0.2% 0.2% 0.0% 0.0% 0.2% 0.0% 0.0% > 10
1.0% 1.0% 0.0% 0.0% 1.0% 0.0% 0.0% 5 to 10
2.0% 2.0% 0.0% 0.0% 2.0% 0.0% 0.0% 5 to 10
3.1% 3.0% 0.1% 3.3% 3.1% 0.0% 0.0% < 5
4.3% 4.2% 0.1% 2.4% 4.3% 0.0% 0.0% < 5
5.3% 5.2% 0.1% 1.9% 5.3% 0.0% 0.0% < 5
116
From the previous analysis it can be concluded that, considering a resolution of 0.1%,
there is no error in the measurement compared with the pattern equipment, however, the
voltage difference of the power source contributes ± 0.1% strain to the readings in the strain
range ± 5%.
117
Annex 14
Measurement Analysis for Strain Test with Signal Amplification
The analysis of the theoretical error with the signal amplification is shown in the
following table.
Table A14.1 Error Estimation with Signal Amplification.
VEX (V) VO /10 (V) GF Strain Strain (μɛ) Resolution (μɛ) Theoretical
Error
4.9 0.000293636 2.155 -0.01% -111 -100 -10%
5 0.000293636 2.155 -0.01% -109 -100 -8%
5.1 0.000293636 2.155 -0.01% -107 -100 -6%
4.9 -0.000293636 2.155 0.01% 111 100 -10%
5 -0.000293636 2.155 0.01% 109 100 -8%
5.1 -0.000293636 2.155 0.01% 107 100 -6%
The operational amplifier used to establish the amplification was the INA114 BP.
This amplifier can be fed with 5V that will be taken from the regulator output already
implemented and the Gain (G) of the circuit is given by the following equation.
𝑮 = 𝟏 +𝟓𝟎 𝑲Ω
𝑹𝑮 (A14 1)
With resistance of 5 Ohms, the value of the gain would be 11, a value very close to
the amplification of 10 expected. The following images show the amplifier circuit connected
to the bridge output.
Figure A14. 1 Bridge Transducer Amplifier Circuit.
118
Figure A14. 2 Bridge Transducer Amplifier Circuit Implementation.
Once the connection of the amplifier to the measuring circuit was made, the gain was
verified by making measurements close to the mV in strain range of ± 5%.
Figure A14. 3 Gain Tests for Strain Measurement.
For these tests, two multimeters (OTC series 55 and MUL-280) and the B & K
3160-A module were used. The results of the tests are presented in the following table.
119
Table A14. 2 Circuit Gain Analysis.
OTC 55 Vo (mV)
B&K 3160A
Vo (mV)
MUL-280 Vo (mV)
Gain B&K
Error B&K Gain
MUL-280 Error
MUL-280
131.4 1100 1191 8.371 -23.90% 9.064 -17.60%
106 1100 1097 10.377 -5.66% 10.349 -5.92%
80.2 893 885 11.135 1.22% 11.035 0.32%
47.2 527 523 11.165 1.50% 11.081 0.73%
24.3 270 267.7 11.111 1.01% 11.016 0.15%
-5.8 -64.5 -63.9 11.121 1.08% 11.017 0.16%
-20.6 -230 -227.8 11.165 1.50% 11.058 0.53%
-57.5 -641 -631 11.148 1.34% 10.974 -0.24%
-81 -892 -883 11.012 0.11% 10.901 -0.90%
-108.4 -941 -928 8.681 -21.08% 8.561 -22.17%
-134.3 -922 -909 6.865 -37.59% 6.768 -38.47%
From the previous table, it can be said that the amplifier fulfills its function in the
range of ± 900 mV, this means that the range of reliable voltage variation at the output of the
Wheatstone bridge would be ± 90 mV. The following graph allows to visualize this.
Figure A14. 4 Circuit Gain Analysis..
120
It is important to relate the measurements made with the strain, so by applying the
values above to equation A12 6 (Annex 12) and considering a power source of 5 V, gage
factor (GF) of 2,155 and gain (G) of 11, the following results are obtained.
Table A14.3 Circuit Gain Analysis – Strain Conversion and Error Calculation.
VEX (V)
GF G
Multimeter OTC 55
B&K 3160 A MULTIMETER MUL-280
Vo (mV)
Strain Vo
(mV) Strain Error
Vo (mV)
Strain Error
5 2.155 11 131.4 -4.6% 1100 -3.57% -21.90% 1191 -3.85% -16.87%
5 2.155 11 106 -3.8% 1100 -3.57% -6.02% 1097 -3.56% -5.69%
5 2.155 11 80.2 -2.9% 893 -2.92% 0.30% 885 -2.89% 0.31%
5 2.155 11 47.2 -1.7% 527 -1.75% 0.71% 523 -1.73% 0.72%
5 2.155 11 24.3 -0.9% 270 -0.90% 0.15% 267.7 -0.89% 0.15%
5 2.155 11 -5.8 0.2% -64.5 0.22% 0.16% -63.9 0.22% 0.16%
5 2.155 11 -20.6 0.8% -230 0.78% 0.53% -227.8 0.78% 0.53%
5 2.155 11 -57.5 2.2% -641 2.21% -0.24% -631 2.18% -0.24%
5 2.155 11 -81 3.1% -892 3.11% -0.93% -883 3.08% -0.93%
5 2.155 11 -108.4 4.2% -941 3.29% -29.36% -928 3.24% -22.95%
5 2.155 11 -134.3 5.3% -922 3.22% -65.11% -909 3.17% -39.78%
With the data presented, in the range of ± 3% of strain the error is below 5%, however
out of this range the error is much greater than 5%, this can be seen in the following figure.
Figure A14. 5 Error vs. Strain relationship with amplifier circuit.
121
If strain is related to gain, the following graph shows that in a range of approximately
± 3% strain, the gain of 11 is maintained.
Figure A14. 6 Strain vs. Gain relationship with INA 114 BP amplifier circuit.
122
Annex 15
Prototype Operation Manual
This manual considers that the prototype will take measurements of sensors with
voltage variation or the instrumentation is carried out to measure acceleration or deformation
with the following components:
Table A15. 1 Instrumentation - Components
Measurement Instrumentation
Acceleration
NI cRio -9030
NI 9206 module
RC Low Pass Filter
Fc 338 Hz
Silicon Design Accelerometer model 2220-100
Strain
NI cRio -9030
NI 9206 module
RC Low pass Filter
Fc 338 Hz
Voltage Regulator LM 7805
Micro Measurements MR1-350-172 module
Micro Measurements CEA-06-125UN-350 Strain Gage
Other Sensor with voltage range variation ± 5 V
123
The details of the parts forming the device are shown below.
a.
b.
Figure A15. 1 a.- Side view details b.- Top view details
124
Once the instrumentation has been implemented, the following steps must be
followed to configure the prototype:
1. Power the equipment by connecting it to DC supply (9 to 30 V) or to 110 V
AC supply. Note. - Do not turn on the equipment with both power supplies at
the same time.
2. Connect the DAQ system to the computer via an Ethernet cable and establish
the connection with the equipment.
Figure A15. 2 Route to stablish connection with the prototype.
3. Connect a USB drive where the tests will be stored.
4. To establish communication with the truck's ECU, the connector must be
connected under the SAE J 1939 protocol. Check the truck manufacturer's
manual to find its location that is usually below the driver's dashboard.
5. Open the user interface and on the first tab enter the general information of
the test.
125
Figure A15. 3 General Information Tab.
6. Identify and activate the channels that will perform the measurement with the
device.
Figure A15. 4 Sensors Selection Tab.
7. In the second tab, each channel contains a box to configure details of the
parameter to be measured, in this box the parameter to be measured, the sensor
126
and its series will be configured, as well as the sensitivity that in the case of
acceleration should be in mV / g while for strain or other parameter it should
be 1.
Figure A15. 5 Channel Configuration Box.
8. Select if you want to calibrate the offset of the measurement before starting
the test.
Figure A15. 6 Calibration Option.
127
9. Select if you wish to reset the parameters at the end of the test.
Figure A15. 7 Reset Option.
10. Define the sampling rate as well as the name of the file to be generated.
Figure A15. 8 Sampling Frequency and File Name Definition.
11. Then, in the CAN tab, the parameters required from the ECU´s unit are
selected.
128
Figure A15. 9 CAN parameters selection.
12. Once the parameters of the test have been defined, if the offset calibration
option is chosen, the truck must be switched off, otherwise the offset could be
calibrated manually. To Run the program, click on Play.
Figure A15. 10 Run Test.
13. The device will begin with the acquisition of data. To stop the test, click on
Stop.
Figure A15. 11 Stop Test.
129
14. At the end of the test do not remove the USB memory until the play button is
activated again, this to give the computer time to record the information.
15. The information will be stored in a .tdms format file in which the information
entered and the readings of the enabled sensors will be included. This
information is ready to be treated and interpreted by the technician.
130
Appendixes
Appendix A
131
132
133
Appendix B
134
Appendix C
135
Appendix D
136
137
Appendix E
138
Appendix F
139
140
Appendix G
141
142
143
144
Appendix H
145
Voltage regulator circuit.
146
Appendix I
![DCU 305 R3 CAN / J1939 Manual - Auto-Maskin§ [a] SAE, J1939-71 § [b] SAE, J1939-73 § [c] Conrad Etschberger, “Controller Area Network” ... CAN / J1939 Manual CAN / J1939 –](https://img.pdfslide.us/doc/110x75/5ae535d97f8b9a7b218f6863/dcu-305-r3-can-j1939-manual-auto-maskin-a-sae-j1939-71-b-sae-j1939-73.jpg)
