ReferencesGAS INSULATED TRANSFORMER

A report submitted in partial fulfillment of the requirements for the Degree ofBachelor of Technology in Electrical Engineering

Submitted By

Rajesh Kumar MohapatraRegd. No. -1141013244Sec-B

Department of Electrical EngineeringINSTITUTE OF TECHNICAL EDUCATION & RESEARCH, BHUBANESWAR(SIKSHA O ANUSANDHAN UNIVERSITY, ODISHA)2014

CERTIFICATE

This is to certify that the project work entitled GAS INSULATED TRANSFORMER carried out by RAJESH KU MOHAPATRA, under my guidance bearing Regd.No-1141013244, a student of 8th Sem. B. Tech. in Electrical Engineering from Institute of Technical Education & Research, Bhubaneswar, has completed the seminar.

GUIDE - Mr. Jyotiranjan PadhiDEPARTMENT OF ELECTRICAL ENGINEERINGINSTITUTE OF TECHNICAL EDUCATION & RESEARCH (Under Sikhsa O Anusandhan University, Odisha) Jagamohan Nagar, Jagamara, Khadagiri, Bhubaneswar-751030

HOD - Dr. Renu Sharma

Contents1. CHAPTER 1: INTRODUCTION 1

1.1. Types of BCIs 11.1.1. Invasive BCIs11.1.2. Partially Invasive BCIs21.1.3. Non-Invasive BCIs21.2. Electroencephalography21.2.1. Spontaneous BCIs31.2.2. Evoked BCIs31.2.2.1. P30031.2.2.2. N2PC41.2.3. Comparison of combination of P300 and N2PC potentials4

2. CHAPTER 2: BASIC STRUCTURE OF BCI 5

2.1. Hardware Requirements 52.1.1. g.USBamp Amplifier62.1.2. g.Gamma Cap62.1.3. Computer72.2. Software Requirements8

3. CHAPTER 3: PROCESSING OF SIGNALS 9

4. CHAPTER 4: BCI APPLICATIONS 11

4.1. Internet Application 114.1.1. Machine States of BCI Internet Application124.2. Robot Control Application 134.2.1. Machine States of Robot Control Application114.3. Basic Needs Communication Application 15

5. CHAPTER 5: FUTURE ASPECTS OF BCI 17

6. CONCLUSION 18

REFERENCES 19

ABSTRACT

There has been a rapid increase of gas insulated transformers and reactors in East Asian countries. Plans to construct underground or indoor substations accelerate this trend, because of the difficulty in acquiring spaces for substations in large cities where the electric power demand is concentrated. Requirements of security against fire accidents, compactness and total cost reduction are the key factor for these substations. Total gas insulated substations combining gas insulated switchgears and gas insulated transformers meet these needs. Demand for gas-insulated transformers has been increasing rapidly, particularly in Japan, Hong Kong and China. More than 10,000 units and up to 275 kV-300 MVA class of gas-insulated transformers are currently operating in the field. The first gas-insulated transformer in Japan started operation in 1967. These transformers finished their function satisfactorily in 1990s. These facts indicate that the gas insulated transformer technology has been well matured and proven.

List of Figures

Fig. 1.1Invasive BCI 1Fig. 1.2Partially Invasive BCI 2Fig. 1.3Non-Invasive BCI 2Fig. 2.1Block Diagram of BCI 5Fig. 2.2Amplifier 6Fig. 2.3EEG Cap 6Fig. 2.4BCI user using the Internet application 7Fig. 3.1Data Pane 10Fig. 3.2Parameters Pane 10Fig. 3.3Details Pane 10Fig. 4.1Internet Application Virtual Keyboard 11Fig. 4.2Internet Application Virtual Mouse 11Fig. 4.3Internet Application Distance Selection 12Fig. 4.4Internet Application Machine States 12Fig. 4.5User using a robotic arm application 13Fig. 4.6Robot Control Application Action Menu 14Fig. 4.7Robot Control Application Distance Selection 14Fig. 4.8Robot Control Application Confirmation Menu 14Fig. 4.9Robot Control Application Machine States 15Fig. 4.10Basic Needs Communication Application 15

CHAPTER 1IntroductionA brainmachine interface (BMI) [1], also known as mind-machine interface (MMI) or sometimes direct neural interface or braincomputer interface (BCI), is a direct communication pathway between the brain and an external device. BCIs are directed at assisting, augmenting, or repairing human cognitive or sensory-motor functions. Assistive technology is a very important help for paralyzed people or people with motor neuron diseases. This technology allows them to increase their independence and also improves their quality of life. With the recent development of BCI applications, people can access internet applications, operate robotic arms and even communicate with other people using basic commands related to emotions and needs. All this can be done by a person just by thinking or focusing about a certain option available from several in the application being used.1.1 Types of BCIs

BCIs can be invasive, partially invasive or non-invasive in nature.

1.1.1 Invasive BCIs

Figure 1.1: Invasive BCIInvasive BCIs [2] are implanted directly into the grey matter of the brain during neurosurgery. As they rest in the grey matter, invasive devices produce the highest quality signals of BCI devices. However, they pose medical risks and are prone to scartissue build-up, causing the signal to become weaker or even lost as the body reacts to a foreign object in the brain.

1.1.2 Partially Invasive BCIs

Figure 1.2: Partially Invasive BCIPartially invasive BCI [2] devices are implanted inside the skull but rest outside the brain rather than within the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scartissue in the brain than fully invasive BCIs.

1.1.3 Non Invasive BCIs

Figure 1.3: Non-Invasive BCIAs well as the invasive experiments, there are also non-invasiveBCIs [2] such as neuro-imaging technologies. Signals recorded in this way have been used to power muscle implants and restore partial movement in an experimental volunteer. Although they are easy to wear, non-invasive implants produce poor signal resolution because the skull dampens signals, dispersing and blurring the electromagnetic waves created by the neurons. Although the waves can still be detected it is more difficult to determine the area of the brain that created them or the actions of individual neurons.For humans, however, non-invasivemethods are preferable because of ethical concerns and medicalrisks.

1.2 Electroencephalography (EEG)

Electroencephalography (EEG) [1] is the study ofthe electrical brain activity recorded from electrodesplaced on the scalp. It is the most studied potential non-invasive interface, mainly due to its fine temporal resolution, ease of use, portability and low set-up cost. The main source of the EEG is the synchronousactivity of thousands of cortical neurons. These signalsare characterized by small signal amplitudes (a few lVolts) andnoisy measurements. Despite their poor signal-to-noise ratio,recent experiments have shown that EEG provides enough informationto interact with devices.

Non invasive BCIs can be classified as spontaneous or evoked.

1.2.1 Spontaneous BCIs

Spontaneous BCIs are based on the analysis of EEG phenomenaassociated with various aspects of brain function relatedto mental tasks carried out by the subject at his/her own will.Some researchers measure slow cortical potentials over the topof the scalp. Other groups look at EEGrhythms recorded from the central region of the scalp overlyingthe sensory-motor cortex during the imagination of body movements. But, in addition to motor-related rhythms, other cognitive mentaltasks have been explored, such as mental rotation of geometric figures,arithmetic operations, or language to develop BCIs.

1.2.2 Evoked BCIs

Evoked BCIs are based on the extraction of acharacteristic EEG signal pattern produced automatically in thebrain as response to some external stimuli.Two evoked potentials widely explored in the field of BCI are the P300 and N2PC.

1.2.2.1 P300

P300 [3] is a potential evoked byan awaited infrequent event and it is characterized by a positive deflection in the EEG signal approximately produced 300 millisecondsafter receiving a visual stimulus. This paradigm was first usedin 1998 to develop a speller application.However, recently this paradigm has been used on other applications,such as controlling a wheelchairor Internet browsing applications.

In these applications, in order toevoke the P300, subjects are given a sufficiently large number ofoptions like letters of the alphabet or icons from which theychoose one by paying attention to the desired one. These optionsare pseudo-randomly flickering in a screen and it is possible todetermine which choice the subject intended as a target, simplyby selecting the stimulus that elicits the largest P300.1.2.2.2 N2PC

N2PC [4] is another evoked potential which is a negative deflection inthe EEG, produced approximately 200 seconds after a visual stimulus.This potential has not been used yet to control BCI systems,although has been widely studied to prove its relationship withselective attention.

The main goal of this report is to describe a non-invasive BCIbased on the P300 and N2PC paradigm that allows controlling devicesand interacting with people without any motor muscularmovement.

1.2.3 Comparison of Combination of P300 and N2PC potentials

Table 1.1: Hit Rate using different combination of P300 and N2PC potentialsUsersP3005 ElectrodesHit Rate (%)N2PC8 ElectrodesHit Rate (%)P300 + N2PC16 ElectrodesHit Rate (%)

User 16095100

User 2757186

User 39386100

The above table gives the results obtained by three healthy volunteers.The results obtained indicate that it is possible to developa BCI application by only using the N2PC potentials. The hit rateusing this potential is almost the same, or even better in somecases than the hit rate obtained using the P300. However the drawbackis that the number of electrodes is higher. On the other hand,the results obtained using both potentials are better than by usingonly one of them. Therefore the combination of both potentials is auseful tool for increasing the hit rate of the BCI.

Introduction

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CHAPTER 2Basic Structure of BCI

Figure 2.1: Block Diagram of BCI

The BCI consists of a signal extractor which extracts the brain signals via an EEG cap and electrodes.There is a preprocessing unit which consists of an amplifier to amplify and digitalize the obtained signals and a feature extraction block which consists of filters to select the most significant signals, which are in turn sent to the classifier for training and testing of data. The classified data is associated with the application interface which works accordingly.The basic requirement of a BCI is the brain signals which can be obtained if the user focuses on a particular option. Then, the corresponding signals are extracted [5] and processed. The processing includes signal amplification and digitalization.Next, the features are extracted; this process involves filtering and finally classification using a classifier [6] after which the application interface is operated.2.1 Hardware RequirementsThe main devices used in the BCI are based on the commercial devices from g.tec [7](Guger Technologies). g.tec is an active member in a number of national and international research projects and is active in scientific publishing. It developed the first commercially available BCI system in 1999 and now sells this system in more than 60 countries worldwide. The g.tec team tests different BCI technologies on more than 500 subjects internationally to guarantee a perfect working system. The devices used in BCIs are depicted in the following pages.2.1.1 g.USBamp Amplifier

Figure 2.2: Amplifierg.USBamp [8] is a highperformance and highaccuracy bio-signal amplifier and acquisition/processing system. It allows movements, respiration, galvanic skin response and many other physiological and physical parameters. Due to its technical specifications and various software options, this instrument became a standard for many different fields of research, including neuropsychology, life science, medical research and BCI research.The amplifier connects easily to the USB socket on a PC/notebook and can immediately be used for data recording. A synchronization cable guarantees that all devices are sampling with exactly the same frequency. The amplifier has an input range of 250 mV, which allows recording of DC signals without saturation. Digital inputs and outputs allow the recording of trigger channels together with the biosignal channels to easily pass analysis results to the outside world.2.1.2 g.GAMMAcap

Figure 2.3: EEG Cap g.GAMMAcap [9] is designed for maximum comfort for the subject and fastest receival of brain signals. The fabric used for the cap is flexible but robust. An EEG cap with 64 positions based on the 10/20 system is used to placethe electrodes on the scalp of the person. In addition, special abrasiveand conductive gels are used to improve the contact skin/electrodereducing impedances.The gel is inserted through the hole in the middle of the electrode. All types of active and passive electrodes can be replaced if necessary. The electrodes normally stay inside the cap and are also cleaned with the cap.

2.1.3 ComputerThe amplifier is connected to acomputer with the specifications of the computer as Intel Core 2 Duo 1.87 GHz, 1 GB DDR RAM, WindowsXP by USB. Other specifications supported by BCI include the following. Windows 7 Professional Edition 32-bit English version Windows 7 Professional Edition 64-bit English version Linux Ubuntu 12.04 LTS 32-bit English version Linux Ubuntu 12.04 LTS 64-bit English version LabVIEW 2011 32-bit English Version LabVIEW 2011 64-bit English Version MATLAB Release 2012a 32-bit version

This computer is used to process and classify the EEG signals. Fig.7shows the hardware of the BCI.

Figure 2.4:BCI user using the Internet applicationThe computer has two screens: one shows the BCIapplications developed (user screen), while the other shows theconfiguration options for the controller (controller screen).

2.2 Software RequirementsThe BCI2000 software [1] is used for sampling, processing and classifying the EEG signals. This open source software platform for general purpose consists of a series of independent modules, each of them responsible for a concrete function. g.tec provides Windows-based recording software to MATLAB/SIMULINK and LabVIEW Highspeed Online-Processing environment and device drivers as well as APIs. g.USBamp is also supported by some open source research communities such as OpenVibe and BCI2000.

Basic Structure of BCI

CHAPTER 3Processing of SignalsThe EEG signals obtained by means of the EEG cap and electrodes are amplified and digitalized The EEG signals are amplified and digitalized with a sample frequencyof 256 Hz using 8 bits per sample. Afterwards, a band-passButterworth IIR filter is applied between 0.1 and 30 Hz. Inaddition, a Notch filter (reject-band) between 48 and 52 Hz is also applied to avoid electromagnetic interferences producedby the power line. In spite of being enough by applying theButterworth filter to avoid electromagnetic contribution at 50 Hz,the Notch filter is applied for security issues. The combinationof both filters does not spoil the quality of the signals since themain frequency of the evoked potentials is located below 30 Hz.These filters smooth the signals and reject non useful informationfrom the EEG, improving the detection of the evoked potentials.Then, a temporal filtering is applied to the signal produced aftereach visual stimulus. The evoked potentials are time variant butbounded, so the filter is configured to consider the first 600 msas study time. After each series of visual stimuli corresponding toa decision, the average of all the segments of 600 ms for eachstimulus is calculated, removing the background activity, possibleartifacts and isolating repetitive patterns. The new signal is the resultof this average and it is composed of 153 samples by channel.Afterwards the signals are decimated at 20 Hz.After this decimation,there are a total of 192 samples.The 60 most significant samples from the 192 are statistically chosen by the programused to classify the signals. This way, approximately 4 samplesare used per channel.The signals are classified using the P300 classifier[10] which uses the Stepwise Linear Discriminant Analysis algorithm (SWLDA) [5].The samples collected after filtering are entered in the data pane (Fig.8) of the classifier along with the training data. The process of classification is carried out on these signals in the parameters pane (Fig.9) and finally the output is obtained in the details pane (Fig.10).

Figure 3.2: Parameters PaneFigure 3.1:Data Pane

Figure3.3:Details Pane

Processing of Signals

CHAPTER 4BCI ApplicationsThe three major applications included in this paper are the Internet application, the Robot control application and the Basic Needs Communication application. The basic working procedure of these applications has been described in the following sections.4.1 Internet ApplicationThe Internet application [1] gives the user the full control of a Windows-based computer with the Internet browser since the inputs are keyboard andmouse interfaces.The application has several selection menus from which rowsand columns are randomly flashing. The user has to fix his/her gaze on one option of these menus to choose the desired item.These menus consist of virtual devices that allow the same interactionwith the computer as the real keyboard or mouse.The selectionmenus or selection matrices used in the application are shown and described below.

Figure 4.2: Internet Application - Virtual Mouse

Figure 4.1: Internet Application - Virtual Keyboard

Figure 4.3: Internet Application - Distance Selection

The virtual keyboard,an 11x4 matrix consists of all the basic keys for introducing numbers and characters as wellas to change to virtual mouse or distance selection menu. Virtual mouse, a 5 x 3 matrix comprises of icons for eight possible directions,right and left clicks, double left click, scroll up and down andread mode in which the system will return to the virtual keyboard.The distance control menu, a 3 x 3 matrix consists of nine options with differentdistances of movement for the cursor, from 2 to 800 pixelsin different intervals.

The application is shown at the bottom part of the computerwith a 1024 x 768 resolution. The width of the application fitsthe screen and it is 250 pixels high. This way the user has two thirds ofthe screen for Windows or Internet browsing.

4.1.1 Machine States of BCI Internet Application

Figure 4.4: Internet Application - Machine StatesThe given figure (Fig. 14)depicts the machine states [1]of the application. The applicationstarts showing the virtual keyboard i.e. the Wait Keyboard state.From that moment the computer will not execute any action fromthe real input devices. When a character is selected from the virtualkeyboard, the system will change to the Keyboard Action state,where the computer will write the desired letter. When the change tomouse menu key is selected, the system will change to the Wait Mouse state. In this menu, the commands that can be executed with a single option will change the system to the Mouse Actionstate. However, if the selection is cursor movement, the distance control menu will appear and the system willtransfer to the Waiting Distance state. After the distance selectionis done, the system will execute the cursor movement changing back to the Mouse Action state. Once the movements and actions related tothe mouse are finished, the user can go back to the virtual keyboardselecting the Keyboard command on the mouse menu,returning to the initial state.

4.2 Robot Control Application

The robot control application [1] allows disabled people to control a robotic arm.The application allows controlling a robotic arm in order to help disabled people to manipulate objects or perform pick and place tasks. The following picture (Fig.15) depicts a user using the robotic arm to manipulate objects.

Figure 4.5: User using a robotic arm applicationLike the Internet application, this application also uses three menus Action menu (Fig.16), Distance selection menu (Fig.17) and the confirmation menu (Fig.18).

Figure 4.7: Robot Control Application Distance SelectionFigure 4.6: Robot Control Application - Action Menu

Figure 4.8:Robot Control Application - Confirmation MenuThe actions menu, a 4 x 3 matrix has several options to move therobot end-effector in 3D space and to open or close the gripperplaced in the robot end-effector. It also includes options to change the orientation of the robotic arm and a Home button to return the robot to its original position. The distance selection menu, a 3 x 3 matrix selects the distance the robot has to move. Finally, the confirmation menu, which consists of two options Yes and No to confirm the execution of an action.

4.2.2 Machine States of Robot ControlApplication

Figure 4.9: Robot Control Application Machine StatesThe applicationstarts by showing the actions menu i.e. the Waiting Action state.At that time the robot is in the Home position. If the user selectsa basic option of movement, the application will show the distancecontrol menu and the state will change to Waiting Interval state. Once the distance is selected,the robotic arm will be moved and the actions menu willbe shown again. The options to open/close the tool, to move the robotto Home or to change the orientation of the end-effector ofthe robot needs an additional confirmation before being executed.This confirmation is selected by the user using the third menu thatonly shows the options Yes/No.

4.3 Basic Needs Communication Application

Figure 4.10: Basic Needs Communication ApplicationThe Basic Needs Communication application [1] has been developed using the BCI to allow severely disabled people tointeract with others using basic commands related to emotionsand needs. Using this application, users are able to answer simple questions to explain their needs.This application has a selection menu that shows the availableoptions where the user has to concentrate his/her attention whilerows and columns are randomly flickering (Fig.20). The menu, a 6 x 4 matrix is composed of several icons related to emotionalstates and needs. These icons are divided into the categories of emotional states (happy, sad, angry, sleepy, I am hot, I am cold), basic needs (hunger, thirst, washroom, help, emergency and pain), playful needs (TV, music, walk, thanks, hello, bye), confirmation (Yes, No) and icons to change to other menus.

When the user concentrates on one of the characters or optionsthat are flickering on the screen, the system starts the featuresextraction of the signal and average the signals produced by eachsymbol. When all the options have flashed 12 times (6 per rowand 6 per column) the classifier determines the desired optionand the application executes the action associated.

BCI Applications

CHAPTER 5Future Aspects of BCI

The future work in the field of BCI will be based on the improvisation of the existing applications.The Internet browsingapplication, for instance is planned to include a predictive model of words in orderto reduce the required time to write words.In case of the P300 classifier, the present classification results are based on topographies and graphs in the Matlab-based P300 GUI. The future may see the P300Classifier GUI work with frequency-based features. Also, it may be tried to speed up the P300Classifier GUI by using multithreading while solving the Least Squares.In order to increase the operating speed of the interface which is dependent on the speed of detecting EEG signals, ways to detect the EEG signals at a faster rate will have to be found.Moreover, differentstudies will be performed to check the impact of reducing thenumber of electrodes. This reduction is an important issue in orderto reduce the set up time of the system.It is also hopeful to see an increase in the use of these devices in the future. With the advancement in technology, it is expected to see these applications being used on a larger scale and not just on clinical trials by paralyzed or severely disabled people.

Future Aspects of BCI

ConclusionBrain Computer Interface or the BCI is an assistive technology used, a channel established between the human brain andcomputer or computer controlled electronic devices for communication purpose. It cantranslate peoples intent into meaningful action in the real world solely by processingtheir brain waves.In this report, we have seen the different types of BCIs available, the need for non-invasive BCIs, the basic structure of BCIs and most importantly, the process of acquiring and processing brain signals used in the BCI devices. The working of three major BCI applications namely the Internet application, the Robot Control application and the Basic Needs Communication application have also been included.The scope of the BCIs in future has also been discussed along with the areas of their improvement and future expectation of the humankind from these devices.BCIs have revolutionized the very existence of paralyzed and severely disabled people, giving them an opportunity to be partially independent and improve their quality of life.

Conclusion

References

[1] J.L. Sirvent Blasco , E. Iez, A. beda, J.M. Azorn, Visual evoked potential-based brainmachine interface applications to assist disabled people, Expert Systems with Applications, Vol. 39, pp. 7908-7918, 2012[2] Brain-computer Interface, en.wikipedia.org/wiki/Brain-computer_interface[3] P300 (neuroscience), en.wikipedia.org/wiki/P300_(neuroscience)[4] N2pc, en.wikipedia.org/wiki/N2pc[5] Kun Li, Advanced Signal Processing Techniques for Single Trial Electroencephalography Signal Classification for Brain Computer Interface Applications, Graduate School Theses and Dissertations, Paper 3484, 2010[6] A B Schwartz et al., Extraction algorithms for cortical control of arm prosthetics, Current Opinion in Neurobiology, Vol. 11, 2001[7] http://www.g.tec.at/Company/Company-Profile[8] http://www.gtec.at/Products/Hardware-and-Accessories/g.USBamp-Specs-Features[9] http://www.gtec.at/Products/Electrodes-and-Sensors/g.GAMMAsys-Specs-Features[10] http://www.bci2000.org/wiki/index.php/User_Reference:P300Classifier