iv

CERTIFICATE i

ACKNOWLEDGEMENT ii

ABSTRACT iii

TABLE OF CONTENTS iv

LIST OF FIGURES ix

LIST OF TABLES xi

NOMENCLATURE xiv

1 Introduction 1

1.1 General 1

1.2 Causes of Transformer Failure 2

1.3 Importance of Power Transformer Incipient Fault Diagnosis 4

1.4 Methodology of Power Transformer Incipient Fault Diagnosis 5

1.4.1 Dissolved Gas-in-Oil Analysis (DGA) 5

1.4.1.1 IEEE Methods Dissolved Gas-in-Oil Analysis (DGA) 9

1.4.1.1.1 Doernenburg Ratio Method 9

1.4.1.1.2 Roger's Ratio Method 11

1.4.1.1.3 Key-Gases Method 13

1.4.1.1.4 Total Dissolved Key-Gas Concentration Method 14

1.4.1.1.5 Oil-Immersed Paper Insulation Deterioration

Condition Estimation

17

1.4.1.2 IEC Methods for Dissolved Gas-in-Oil Analysis (DGA) 18

1.4.1.2.1 IEC Ratio Method 18

1.4.1.2.2 Duval's Triangle Method 20

1.4.1.3 Other Methods for Dissolved Gas-in-Oil Analysis (DGA) 21

1.4.1.3.1 Denkyoken Method 21

1.4.1.3.2 CIGRE 's Method 22

TABLE OF CONTENTS

v

1.4.1.3.3 Nomograph Method 22

1.4.1.3.4 NBR 7274 Method 22

1.4.1.3.5 IS 10593:2006 Method 23

1.4.1.3.6 Xiaohui Li Method 23

1.4.2 On-line Partial Discharge (PD) Monitoring 26

1.4.3 Insulation Condition Assessment 27

1.4.4 Combination of DGA and Acoustic Method 27

1.5 The Scope of this Dissertation 31

1.5.1 Areas of Interest 31

1.5.2 Contributions Through the Research 31

1.5.3 Arrangement of this Dissertation 31

1.6 Conclusion 32

2 Literature Review 33

2.1 Introduction 33

2.2 Literature Review 33

2.2.1 Overview on the Conventional Methods for Transformer Fault

Diagnosis and Condition Assessment

33

2.2.2 Overview on the Application of AI Techniques for Transformer

Fault Diagnosis and Condition Assessment

34

2.2.2.1 Application of ANN for Transformer Fault Diagnosis 35

2.2.2.2 Application of Fuzzy for Transformer Fault Diagnosis 42

2.2.2.3 Application of SVM for Transformer Fault Diagnosis 48

2.2.2.4 Application of ANN-FL for Transformer Fault Diagnosis 51

2.2.2.5 Application of SVM-PSO for Transformer Fault Diagnosis 57

2.2.2.6 Application of ANN-ES for Transformer Fault Diagnosis 59

2.2.2.7 Application of ANN-SVM for Transformer Fault Diagnosis 62

2.2.2.8 Application of Wavelet for Transformer Fault Diagnosis 64

2.2.2.9 Application of wavelet-ANN hybrid system for Transformer

Fault Diagnosis

64

2.2.2.10 Application of GA for Transformer Fault Diagnosis 65

vi

2.2.2.11 Application of GA-wavelet hybrid system for Transformer

Fault Diagnosis

66

2.2.2.12 Application of GP-Bootstrap hybrid system for

Transformer Fault Diagnosis

67

2.2.2.13 Application of SVM-Bootstrap hybrid system for

Transformer Fault Diagnosis

68

2.2.2.14 Application of SVM-Rough hybrid system for

Transformer Fault Diagnosis

69

2.2.2.15 Application of EWNs for Transformer Fault Diagnosis 69

2.2.2.16 Application of CMAC for Transformer Fault Diagnosis 70

2.2.2.17 Application of PSO for Transformer Fault Diagnosis 70

2.2.2.18 Application of Artificial Immune Network (AIN) for

Transformer Fault Diagnosis

71

2.2.2.19 Application of ANN-PSO hybrid system for Transformer

Fault Diagnosis

72

2.2.2.20 Application of FFT-ANN based hybrid system for

Transformer Fault Diagnosis

72

2.2.2.21 Application of DST for Transformer Fault Diagnosis 73

2.3 Conclusion 75

3 Methodology 76

3.1 Introduction 76

3.2 Artificial Neural Network (ANN) 76

3.2.1 Introduction to ANN 76

3.2.1.1 ANN Applications 77

3.2.1.2 The Advantages of ANN 78

3.2.1.3 The Disadvantages of ANN 79

3.2.2 ANN Control System 79

3.2.3 Introduction to ANN Diagnostics System 80

3.2.4 The Design Methodology of ANN Diagnostics System 80

3.2.5 Multilayer Perceptrons Neural Network (MLP) 83

vii

3.2.5.1 Design Methodology and Algorithm of MLP 83

3.2.5.2 MLP Based Transformer Incipient Fault Diagnostics

System

85

3.2.6 Learning Vector Quantization (LVQ) 87

3.2.6.1 Design Methodology and Algorithm of LVQ 87

3.2.6.2 LVQ Based Transformer Incipient Fault Diagnostics

System

91

3.2.7 Probabilistic Neural Network (PNN) 92

3.1.7.1 Design Methodology and Algorithm of PNN 92

3.1.7.2 PNN Based Transformer Incipient Fault Diagnostics System 94

3.3 Fuzzy-Logic (FL) 96

3.3.1 Introduction to Fuzzy-Logic 96

3.3.1.1 Fuzzy Logic Applications 96

3.3.1.2 The Advantages of Fuzzy-Logic 98

3.3.1.3 The Disadvantages of Fuzzy-Logic 99

3.3.2 Fuzzy-Logic Control System 100

3.3.3 Introduction to Fuzzy Diagnostics System 106

3.3.4 The Design Methodology of Fuzzy Diagnostics System 106

3.3.5 Fuzzy IEC Ratio Method 108

3.3.6 Fuzzy Key-Gas Method 116

3.4 Support Vector Machine (SVM) 125

3.4.1 Introduction to SVM 125

3.4.2 SVM Control System 125

3.4.3 SVM Classifier 126

3.4.3.1 Linear Support Vector Classifier (SVC) 126

3.4.4 SVM Based Transformer Incipient Fault Diagnostics System 128

3.5 Conclusion 130

4 Results and Discussion 131

4.1 Introduction 131

4.2 Result and Discussions 131

viii

4.2.1 Transformer Fault Diagnostics Using MLP 132

4.2.2 Transformer Fault Diagnostics Using LVQ 139

4.2.3 Transformer Fault Diagnostics Using PNN 143

4.2.4 Transformer Fault Diagnostics Using Fuzzy-Logic 144

4.2.5 Transformer Fault Diagnostics Using SVM 147

4.3 Conclusion 152

5 Conclusions 153

5.1 Conclusion and Importance of Dissertation Work 153

5.2 Future Scope 155

List of Publications 156

References 157

APPENDIX A: Training Sample Data 178

APPENDIX B: Testing Sample Data 183