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S d S i S t fSensors and Sensing Systems for Machine Olfaction – Electronic Nose and Electronic Tongue
Dr. Nabarun BhattacharyyayyC-DAC, Kolkata
nabarun bhattacharya@cdackolkata [email protected]
October 29, 2009
Presentation StructureHuman OlfactionMachine OlfactionElectronic Nose
Design Details and ResultsgElectronic Tongue
Design Details and ResultsgRoadmap for Research in Machine OlfactionConclusion
Human OlfactionThe olfactory region is located in the roof of the two nasal cavities Odours are sensations that occur Odours are sensations that occur when compounds (called odorants) that are carried by inhaled air stimulate receptors plocated in the olfactory epithelium. The mucous lipid, which is prod ced in the olfactor produced in the olfactory epithelium, assists in transporting the odorant molecules.Only volatile materials that are soluble in the mucous can interact with the olfactory
t d d th receptors and produces the signals that our brain interprets as odor.
Machine Olfaction
Attempts to mimic human senses of smell and taste by electronic means are called ymachine Olfaction.Sensors are the most crucial components in a machine olfaction system.Signal conditioning, data acquisition, data, data processing and pattern recognition are the crucial modules of an olfactory sensing systemsystem.
Machine Olfaction System
Human Perception Machine Sensing
Eye: VISION
E SOUND
VISION:Camera
SOUND Mi hEar: SOUND
Skin: TACTILE
SOUND:Microphone
TOUCH: Tactile
SENSES
Nose: SMELL
Devices
SMELL: E-NoseNose: SMELL
Tongue:TASTE
SMELL: E-Nose
TASTE: E-Tongue
About Electronic Nose
Electronic Nose senses complex odours using an Array of Sensors (called “sensor array”): each tuned for
d f f il f l il dodour of a family of volatile compounds.Odour stimulus imprints a characteristic electronic pattern as fingerprint (or smell print) on sensor arraypattern as fingerprint (or smell print) on sensor array. This smell print is statistically classified and resolved with suitable pattern recognition engine as a p g gmeasurement of odour of the sample.
In short, Electronic Nose is
“A scientific, reliable, repeatable, physical, non-invasive, affordable real-time techniques for various applications
like food quality assessment, environmental polution detection, medical applications, explosive detection etc.
Basic Block Diagram
Odour Delivery Sensor Array Signal System Conditioning
Data ClassificationAcquisition
Id ifi iIdentification
Od H dli & D liOdour Handling & Delivery
Headspace Sampling
Autosampling StageAir
Mass FlowController
S1
S2 S3Solenoid Valves
Sensor Cell
MeasurementCircuit
Bubbler System
TemperatureControlledBath
SyringeNeedles
Liquid Sampleq p
SSensors
Desirable Properties of electronic nose sensorselectronic nose sensors
Selectivity : Must respond to a range of chemical species.Sensitivity : Should be sensitive to detect vapour concentration range of ppm or ppbconcentration range of ppm or ppb.Speed of Response : Response time should be in the range of secondsthe range of seconds.Reproducibility : Sensors response characteristics should be reproducible.pReversibility : Should be able to recover immediately after exposure to gas.Portability : Should be small so that less sample volume may be used.
Sensors for Electronic Nose
Conductometric or Resistive
Conductance/Resistance
MOS, CP
Capacitive Capacitance PEUT Coated Electrodes
Potentiometric EMF/Voltage MOSFETGravimetric Mass/Pizeoelec SAW / QCM
tricityCalorimetric Temperature Pellisters,
ThermopileOptical RI/Wavelength
/I t it fSurface Pl/Intensity of
RadiationPlasma Sensor
Sensors for Electronic Nose
Amperometric Current Microfuel Cells/Cells/ Polarographic Sensors
Flourescent Type
Optical intensity,
Optical fibres deposited with
florescence etc.
flourescent indicator dye.
Sensors
Conducting polymer micro-sensors - Features
Conductance is altered significantly by
sensors Features
g y yinteraction with vapour species.Sensors are fabricated by electro-polymerization in controlled mannerDifferent polymers show non-overlapping selectivity to different chemicals.Fast response time with excellent reversibility
Conducting polymer micro-sensors - Advantagessensors Advantages
Excellent reproducibilityWide selectivityHigh sensitivityHigh sensitivityWide range of applicationsSt blStableLow powerOperate at ambient temperature
Metal Oxide Sensors -FeaturesFeatures
MOS are semiconducting sensing elementsmade from a metal oxide film e g tin oxidemade from a metal oxide film, e.g., tin oxideMOS operate in the range from 300 oC to500oC500 CThe sensors require O2 to functionVolatiles undergo redox reactions at thegsensor surface, resulting in a change ofconductivity across the sensorS l ti it b difi d b d i thSelectivity can be modified by doping themetal oxide (e.g with Pd, Pt) or modifying theoperating temperature of the sensoroperating temperature of the sensor
Metal Oxide Sensors -Advantages
Longevity
AdvantagesLongevitySensitivityLow response to RHLow response to RHWide range of applicationsLarge response and good discriminating power
Bulk Acoustic Wave Sensors - FeaturesSensors - Features
Quartz crystal can be coated with a wideQuartz crystal can be coated with a widerange of different selective coating filmsOn adsorbing analytes the additional mass ofOn adsorbing analytes the additional mass ofthe film results in a change in the frequencyof oscillation of the sensorA typical sensor has an operating frequencyof about 10 MHz
Bulk Acoustic Wave Sensors Advantages
High selectivity
Sensors - Advantages
Able to measure both polar and non-polarspeciesStable over a wide temperature rangeLow power (low mW)Low sensitivity to humidityHigh stabilityGood reproducibilityWell characterised coating chemistry
Intelligent Pattern Analysis
StatisticalMethods
Quantitative Supervised MLR, PLS
Pattern Analysis Unsupervised PCA CAPattern Analysis Unsupervised PCA, CA
Supervised DFA, PCR
Biologicallyinspiredmethods
ANN Unsupervised SOM
Supervised MLP, PNN, RBF,p , , ,LVQ
Fuzzy Methods Supervised FIS, FNN, FCM
Self-supervised ART, FuzzyARTMAP
Others Self-supervised GA
Supervised NFS, Wavelets
Intelligent Pattern AnalysisAnalysis
PCA – Principal Component AnalysisPLS – Partial Least SquareMLR – Multiple Linear RegressionPCR – Principal Component RegressionPCR – Principal Component RegressionDFA – Discriminant Function AnalysisLDA – Linear Discriminant AnalysisANN – Artificial Neural NetworkSOM – Self Organizing MapGA Genetic AlgorithmGA – Genetic AlgorithmART – Adaptive Resonance TheoryRBF – Radial Basis FunctionNFS – Neuro Fuzzy System
Applications of Electronic NoseNose
Environmental monitoringo Monitoring of air, water and land.Medical Diagnostics andgHealth Monitoringo Breath Monitoringo Breath Monitoringo Eye Infectiono Medical Environmental Monitoringo Medical Environmental Monitoringo Leg Ulcers
Cultured Bacteriao Cultured Bacteria
Electronic Nose applicationsapplications
Food and Beverage Applicationso Quality and process monitoring of fruits vegetableso Quality and process monitoring of fruits, vegetables,
meat, fish, brewery, coffee etc. through electronic nosehas been reported.
A t ti d A A li tiAutomotive and Aerospace Applicationso Detection of hazardous gas within automobiles,
spacecrafts.spacecrafts.Narcotic Detection.Application in Cosmetics and Fragrancepp gIndustryDetection of ExplosivesMiscellaneous upcoming Applications.
E N f TE-Nose for Tea
Sensor Selection
MOS sensors only have been considered.Procurement of Commercially Available MOS Sensors.Procurement of major
daroma determining compounds of tea.
l lExperimental TrialsFinalization of Sensor Array
MOS Sensors ConsideredTGS 2610 Propane and TGS 2201 DieselTGS 2610 Propane and
ButaneTGS 2201 Diesel
ExhaustTGS 2611 Methane TGS 823 OrganicTGS 2611 Methane TGS 823 Organic
SolventsTGS 2442 Carbon TGS 830 HalocarbonTGS 2442, TGS 203
Carbon Monoxide
TGS 830 Halocarbon Gases
TGS 2620 Alcohol TGS 831 RefrigerantsTGS 2620, TGS 822
Alcohol, Toluene, Xylene
TGS 831 Refrigerants R-21, R-22
TGS 2600 Air TGS 825 HydrogenTGS 2600 Air Contaminants
TGS 825 Hydrogen Sulphide
TGS 2180 Water Vapor TGS 826 AmmoniaTGS 2180 Water Vapor from Food
TGS 826 Ammonia
Aroma Determinants in Tea
1 2 – Phenyl-Ethanol
•Overall aroma of tea is a complex interplay of a number of volatile
Major Aroma Determinants of Tea
1 2 – Phenyl-Ethanol
2 Benzaldehyde
number of volatile flavoury compounds (VFC).
3 ß- ionone
4 Geraniol•TRA reports more than 700 biochemical volatiles
t ib t iti l5 Linalool
6 Linalool Oxide
contribute positively or negatively to tea aroma
•Kawakami et al has 6 Linalool Oxide
7 Terpeniol
•Kawakami et. al. has identified 112 aroma compounds in Darjeeling
btea by GC - MS
Sensor Response to Individual Chemicals1
0.9
1
2-phenyl-ethanolBenzaldehyde
B-ionone
Geraniol
Sensor1-TGS 2610Sensor2-TGS 2620Sensor3-TGS 2611Sensor4-TGS 2600
0.7
0.8 Geraniol
Linalool
Linalool oxideTerpeniol
Sensor5-TGS 816Sensor6-TGS 831Sensor7-TGS 832Sensor8-TGS 823
0.5
0.6
nsor
Res
pons
e
0.3
0.4Sen
0.1
0.2
1 2 3 4 5 6 7 80
Sensor Serial Number
Sensor Response to Smell of Tea
Finalization of Sensor ArrayFi li d f i t fFinalized array of sensors consists of EIGHT Figaro sensors: TGS 816, TGS 823 TGS 831 TGS 832 TGS 2600 TGS823, TGS 831, TGS 832, TGS 2600, TGS 2610, TGS 2611 and TGS 2620
Interface Circuit Diagram
Each sesnsor is a MOSsensor made from a Vc V RL
metal oxide film, e.g.,Tin OxideVolatiles undergo redox R Lgreactions at the sensorsurface, resulting in achange of conductivity
V H
R L
g yacross the sensorEach sensor is reversible.Output of each sensor is
GND
Measurement Circuit with MOS SensorOutput of each sensor iswithin TTL range.
Measurement Circuit with MOS Sensor
Signal Conditioning
The output of the sensors is analogue voltage.The sequentialThe sequential stages,namely,buffering,amplification,filtering,conversion and compensation are accomplished innversion and compensation are accomplished in the USB card used in the system for data acquisition.No additional electronics has been used for this purpose
Data Acquisition
Circuit USB 6009 card from the National Instruments has been used.DAQ system consists of sample and hold circuit anti-aliasing and analoguehold circuit,anti aliasing and analogue to digital conversion module.Analogue to digital resolution: 14bitsAnalogue to digital resolution: 14bitsSample rate :250 Ksamples/second
Signal Pre-processing
Steps of Signal Pre-processing:
Baseline identification and manipulationpCompression
Baseline Handling
Baseline refers to sensor response in no exposure conditionFractional technique of baseline qmanipulation is used for compensation against drift and contrast enhancement.g
)0()()( ss xtx −
)0(
)0()()(
s
sss x
xtxty =
)(s
Compression TechniqueCompression is a preprocessing stage where the response of sensor array is
l d futilized as a feature vector or a fingerprint by reducing the number of ddescriptors.The maximum value vector from the sensor output data has only been considered for data analysis.
=M [ ]max8max1 .............. ii SS
Characteristic Sensors Response
2.5
3
3.5
4
4.5
(V)
PurgingRegion
SaturationRegion
0
0.5
1
1.5
2
2.5
Volta
ge (V
TransientRegion
0 100 200 300 400 500 600 700 800 900-0.5
Time (Values have no significance)
Odour Handling & DeliveryA i i iA mini air compressor is used to develop requisite airflow (5 ml.
PATTERNRECOGNITION IN
COMPUTER
q (Per sec.)Three solenoid valves are used to route the
SOLINOIDVALVE-III
SENSOR ARRAY
SUCTION BLOWER
are used to route the airflow to the sample holder and the sensor AMBIENT
AIR
SOLINOID SOLINOID
VALVE III(V3)
PURGINGAMBIENTAIR
array.A blower is used to reinforce air
ODOURMOLECULES
AIR PUMP
SOLINOIDVALVE-I
(V1)
SOLINOIDVALVE-II
(V2)
AIR
reinforce air evacuation during purging.
AIR PUMP
SAMPLEVESSEL
Illumination Based Heating
The tea sample is heated for 65 seconds
PTFE FIXTUREPTFE FIXTURECOMPUTER WITH OLFACTION
SOFTWARE
secondsTemperature of the sample reaches to 60+/
ELECTRONICINTERFACE FOR
LAMP
ELECTRONICINTERFACE FOR
LAMP
HALOGEN LAMP
FAN AGITATOR
reaches to 60+/-30C35 W miniature
SAMPLEHOLDER
RTD
halogen lamp is usedHeating improves
DC MOTOR &
INTERFACE
ANALOGUEDIGITAL DIGITALUSB INTERFACE
DC MOTOR &
INTERFACE
a g p osensitivity of the system indirectly USB DATA ACQUISITION CARDUSB DATA ACQUISITION CARD
INPUTOUTPUT OUTPUTUSB INTERFACE
A Typical Sniffing Cycle A Typical Sniffing Cycle • Illumination Heating: Catalyses aroma emanation from the teaIllumination Heating: Catalyses aroma emanation from the tea
sample
• Headspace Generation: Ensures adequate concentration of• Headspace Generation: Ensures adequate concentration of volatiles released by tea within the sample holder by blowing regulated flow of air on the sample
• Sampling: During sampling; the sensor array is exposed to a constant flow of volatiles through pipelines.
• Purging: During purging operation, sensor heads are cleared with blow of fresh air so that the sensors go back to their baseline valuesvalues
• Dormancy: The system is kept in suspended animation till the next sniffing cyclenext sniffing cycle.
A Typical Sniffing CycleILLUMINATION HEATINGILLUMINATION HEATING
TIME
HEADSPACEGENERATION TIME
N V
OL
TS
4.0
SAMPLING TIME
PURGING TIMER
RE
SP
ON
SE
I
2 0
3.0
SE
NS
OR
1.0
2.0
TIME IN SECONDS
0 40 80 120 160 200 240 280 320
TIME IN SECONDS
E-Nose Prototype Developed
Sensor array Data acquisition PCBSample container with bayonet fitting
Sensor array Data acquisition PCB
Internal Operation Of E-Internal Operation Of E-Nose…
Olfaction Software
Software features:-Programmable Sequence Control-Dynamic Fermentation Profile Display-Data Logging-Alarm AnnunciationFl ibilit t it t l t th l t t i d t i-Flexibility to permit tea planters themselves to train and customize
the system as per their requirements.
D t A l iData Analysis
About Sensor Array Output⎤⎡ 181211 bbb Sensor responses
during headspace generation
⎥⎥⎥⎥⎥⎤
⎢⎢⎢⎢⎢⎡
282221
181211
......
...
...
bbb
bbb
⎥⎥⎥⎥⎥⎥
⎢⎢⎢⎢⎢⎢
=181211
821
...
...
......
......
hhh
SSS
bbbA
⎥⎥⎥⎥⎥⎥
⎢⎢⎢⎢⎢⎢
282221
181211
......
......
...
...
SSS
SSS
Sensor responses when exposed to tea odour during sampling
⎥⎥⎥⎥
⎦⎢⎢⎢⎢
⎣ 821 ...
......
mmm SSS
Data is 8-dimensionalHeadspace Duration : 30 Seconds and Sampling Duration : 50 seconds0 di d d10 readings are scanned per second
Approximately 800 rows are there in any sniffing data matrix
Data Analysis StrategyMULTIVARIATE DATA
MATRIXMATRIX
DATA EXPLORATION DATA QUANTIFICATION
DATA CO-RELATION
PRINCIPAL COMPONENT
ANALYSIS (PCA)
AROMA SCORE CALCULATION BY 2-
NORM METHOD
AROMA SCORE CALCULATION BY
MAHALANOBISANALYSIS (PCA) NORM METHOD MAHALANOBIS DISTANCE METHOD
BACK ARTIFICIAL NEURAL PROPAGATION NETWORK
RADIAL BASIS FUNCTION
PROBALISTIC NEURAL NETWORK
Results – Different ClonesWell-defined clusters are found in PCA.100% classification accuracy observed yin BP-MLP
Results – Different flavoursPCA hibi di iPCA exhibits distinct aroma clusters for teas having different 0 1
0.15
0.2
teas having different taster scores.Neural networks
0
0.05
0.1
3.60
04%
)
Neural networks exhibit varying classification ability -0.15
-0.1
-0.05
PC
A2
( 3
Taster score 8yas follows:
BP-MLP: 81% – 85% -1 -0.5 0 0.5 1 1.5-0.25
-0.2
PCA1 (96.3448%)
Taster score 5Taster score 7
Taster score 6
RBF: 86% - 91%PNN: 91% - 94%
E-Nose for Tea FermentationOxidation process
Fermentation Process Starts as soon as Tea Leaves’ cells are broken during CTC or Rolling Process
Grassy Smell Turns into Floral Smell in this ProcessGrassy Smell Turns into Floral Smell in this Process
Fermentation duration is very crucial in determining Final Q alit of TeaFinal Quality of Tea.
E-Nose can Monitor Volatile Emission Pattern during Fermentation for automatically determining and announcing the completion of useful fermentation
Sample fermentation profiles by Colorimeter
Results of PCA
Sample fermentation profiles by E-Nose
Fermentation Aroma ProfileMahalanobis Aroma Score
2-Norm Aroma Score
1.2 5
0.40.60.8
1
2-N
orm
m
a S
core
2
3
4
hal
ano
bis
m
a S
core
00.20.4
0 8 16 24 32 40 48 56 64 72 80 88 96 104 112 120
2A
ro
0
1 Mah
Aro
Time in Minutes
Detection of Fermentation Peak
Results
Colorimeter testColorimeter test
Human evaluationHuman evaluationHuman evaluationHuman evaluation
No of Fermentation run 81
Accuracy of detection of Fermentation 95%Summary of Results:
yCompletion time by E-Nose vis-à-vis Colorimeter testAccuracy of detection of Fermentation Completion time by E-Nose vis-à-vis Human E l i
96%
Evaluation
Electronic Tongue : Definition
An An ElectronicElectronic TongueTongue is an instrument which comprises of is an instrument which comprises of electrochemical cell, sensor array and appropriate pattern electrochemical cell, sensor array and appropriate pattern
iti t bl f i i i liti t bl f i i i lrecognition system, capable of recognizing simple or recognition system, capable of recognizing simple or complex soluble noncomplex soluble non--volatile molecules which forms a taste volatile molecules which forms a taste of a sample. of a sample.
The sensor array consists of broadly tuned (nonThe sensor array consists of broadly tuned (non--specific) specific) potentiometric metal based electrode that are treated with apotentiometric metal based electrode that are treated with apotentiometric metal based electrode that are treated with a potentiometric metal based electrode that are treated with a variety of common anion of a salt in solution variety of common anion of a salt in solution –– chemical chemical materials. materials.
Cont…
The Electronic Tongue is consisting of working electrode, reference electrode and counter electrode. Basically, an electrode provides an interface by which a charge can beelectrode provides an interface by which a charge can be transferred. A potential is applied consecutively to each electrode and transient current responses are collected from l t d th h d t i iti delectrode through data acquisition card.
In voltammetric method, a voltage is applied over the working electrode and reference electrode. A current is measured between working electrode and counter electrode.electrode.
Cont……..
Working Electrode: The working electrode is an innert material h G ld Pl i Gl C b I h hsuch as Gold, Platinum, or Glassy Carbon, etc. In these case, the
working electrode serve as a surface on which the electrochemical takes place. It places where redox reaction occur. p pSurface area should very less (few mm2) to limit current flow
Reference Electrode: The reference electrode is used in measuring the working electrode potential. A reference electrode should have a constant electrochemical potential as long as no current flows through it.g
Counter electrode: The counter electrode is a conductor that completes the cell circuit. It is generally innert conductor. The current flows into the solution via the working electrode leaves the solution via the counter electrode. It does not role in the redox reactionreaction.
Supporting electrolyte: salt does not react withSupporting electrolyte: salt does not react with electrodes but has conductivity
Signal appliedSignal applied
LinearDiff i l lDifferential pulseSquare waveCyclic
Sensor of Electronic Tongue
Name of SpecificationName of electrode
Specification
Working Irridium Metal wire 99 9%Working Irridium, rhodium, platinum,
Metal wire 99.9% pure; dia- 1mm
p ,palladium, Gold
Counter Platinum do
Reference Ag/Agclg g
Set of electrode
Electrodes Pin configuration
Electronic Tongue
WateTea
Liquorr
Array of ElectrodesElectrodes
Current Status vis-à-vis Work Plan
11th Plan Project jproposed
Pilot Level Deployment
NTRF Funding
Future Scope of ResearchHybrid sensor array consisting of MOS, CP and QCMand QCMDevelopment of new sensor array sensitive and selective to tea aromaand selective to tea aromaDevelopment of more efficient algorithms f b tt l t i d l ifi tifor better clustering and classificationTechniques for drift compensationIntegration of E-Nose with E-Tongue and E-Vision systems --- ENTV Systemy y
THANK YOUTHANK YOU