Optical Sensing in Power Transformers E-Book

Jun Jiang

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Wiley - IEEE
• Sprache: Englisch

Seitenzahl: 446

Veröffentlichungsjahr: 2020

Beschreibung

A cutting-edge, advanced level, exploration of optical sensing application in power transformers Optical Sensing in Power Transformers is filled with the critical information and knowledge on the optical techniques applied in power transformers, which are important and expensive components in the electric power system. Effective monitoring of systems has proven to decrease the transformer lifecycle cost and increase a high level of availability and reliability. It is commonly held that optical sensing techniques will play an increasingly significant role in online monitoring of power transformers. In this comprehensive text, the authors--noted experts on the topic--present a scholarly review of the various cutting-edge optical principles and methodologies adopted for online monitoring of power transformers. Grounded in the authors' extensive research, the book examines optical techniques and high-voltage equipment testing and provides the foundation for further application, prototype, and manufacturing. The book explores the principles, installation, operation, condition detection, monitoring, and fault diagnosis of power transformers. This important text: * Provides a current exploration of optical sensing application in power transformers * Examines the critical balance and pros and cons of cost and quality of various optical condition monitoring techniques * Presents a wide selection of techniques with appropriate technical background * Extends the vision of condition monitoring testing and analysis * Treats condition monitoring testing and analysis tools together in a coherent framework Written for researchers, technical research and development personnel, manufacturers, and frontline engineers, Optical Sensing in Power Transformers offers an up-to-date review of the most recent developments of optical sensing application in power transformers.

Leseprobe

Table of Contents

Cover

Optical Sensing in Power Transformers

Copyright

Foreword

Preface

Acknowledgments

About the Authors

Acronyms

List of Figures

List of Tables

1 Power Transformer in a Power Grid

1.1 Typical Structure of a Power Transformer

1.2 Insulation Oil in a Power Transformer

1.3 Condition Monitoring of an Oil‐Immersed Power Transformer

1.4 Conclusion

References

2 Temperature Detection with Optical Methods

2.1 Thermal Analysis in a Power Transformer

2.2 Fluorescence‐Based Temperature Detection

2.3 FBG‐Based Temperature Detection

2.4 Distribution Measurement

2.5 Conclusion

References

3 Moisture Detection with Optical Methods

3.1 Online Monitoring of Moisture in a Transformer

3.2 FBG‐Based Moisture Detection

3.3 Evanescent Wave‐Based Moisture Detection

3.4 Fabry–Perot‐Based Moisture Detection

3.5 Conclusion

References

4 Dissolved Gases Detection with Optical Methods

4.1 Online Dissolved Gases Analysis

4.2 Photoacoustic Spectrum Technique

4.3 Fourier Transform Infrared Spectroscopy (FTIR) Technique

4.4 TDLAS‐Based Technique

4.5 Laser Raman Spectroscopy Technique

4.6 Fiber Bragg Grating (FBG) Technique

4.7 Discussion and Prediction

4.8 Conclusions

References

5 Partial Discharge Detection with Optical Methods

5.1 PD Activities in Power Transformers

5.2 FBG‐Based Detection

5.3 FP‐Based PD Detection

5.4 Dual‐Beam Interference‐Based PD Detection

5.5 Multiplexing Technology of an Optical Sensor

5.6 Conclusion

References

6 Other Parameters with Optical Methods

6.1 Winding Deformation and Vibration Detection in Optical Techniques

6.2 Voltage and Current Measurement with Optical Techniques

6.3 Electric Field Measurement

6.4 Conclusion

6.5 Outlook

References

Index

End User License Agreement

List of Tables

Chapter 1

Table 1.1 Insulating properties of different types of transformer oils.

Table 1.2 Gases produced at different fault types.

Chapter 3

Table 3.1 Evanescent field energy ratio of MNF with different diameters.

Chapter 4

Table 4.1 Technical parameters for multi‐gas online monitoring equipment.

Table 4.2 Dissolved gas concentrations at different status.

Table 4.3 Central wavelength of C

2

H

2

, CH

4

, C

2

H

4

, and C

2

H

6

.

Table 4.4 Technical parameters of the specialized Herriott cell.

Table 4.5 Comparison results of developed equipment vs. an existing system on...

Table 4.6 Contrasting analysis of gas concentration detected by the TDLAS equ...

Table 4.7 Spectral lines of the seven fault characteristic gases in transform...

Table 4.8 Detailed parameters of magnetron‐sputtering coating.

Table 4.9 Specifications of various gas sensors for the detection of hydrogen...

Table 4.10 Comparison of conventional gas chromatography and the FBG‐based se...

Table 4.11 Comparisons of various optic‐based gas detection techniques for po...

Chapter 5

Table 5.1 Analysis and comparison of different optical structures in partial ...

List of Illustrations

Chapter 1

Figure 1.1 Power transformers in a typical power grid/schematic drawing of a...

Figure 1.2 Typical structure of a large‐scale oil‐immersed power transformer...

Figure 1.3 Illustration of typical components of typical transformer oil....

Figure 1.4 Roles and properties of insulation oil in power transformer.

Figure 1.5 Time and cost analysis of condition‐based maintenance.

Chapter 2

Figure 2.1 Typical losses in an AC power transformer.

Figure 2.2 Thermal equilibrium in a power transformer.

Figure 2.3 Process to calculate the temperature distribution using a couplin...

Figure 2.4 Typical fluorescence characteristic curve.

Figure 2.5 Typical design of single fiber fluorescent probe.

Figure 2.6 Measurement of temperature based on the optical fluorescence life...

Figure 2.7 Connection illustration of multiple fluorescent temperature measu...

Figure 2.8 Schematic representation of FBG‐based temperature sensing and its...

Figure 2.9 Schematic diagram of a typical FBG temperature sensor probe.

Figure 2.10 Possible locations of the optical FBG sensors.

Figure 2.11 Temperature online monitoring system scheme. Source: Modified fr...

Figure 2.12 Illustration of a multi‐point measurement based on FBGs.

Figure 2.13 Typical spontaneous scattering spectrum in an optical fiber. Rep...

Figure 2.14 Schematic diagram of the Raman scattering phenomenon.

Figure 2.15 The topology and working principle of R‐OTDR. Source: Modified f...

Figure 2.16 Typical distributed sensing fiber based on the winding structure...

Figure 2.17 Transformer temperature monitoring system based on distributed o...

Figure 2.18 The optical fiber winding composite model and the measurement sy...

Figure 2.19 Optical temperature sensing techniques in a power transformer.

Chapter 3

Figure 3.1 Molecule structure of cellulose consisting of glucose rings with ...

Figure 3.2 Water solubility in transformer oil is dependent on the temperatu...

Figure 3.3 Quality standard of transformer oil with regard to moisture conte...

Figure 3.4 Schematic structure of a parallel plate capacitive sensor.

Figure 3.5 Repeat units of a PI molecule and the possible sites for water....

Figure 3.6 FBG‐based sensors for humidity monitoring.

Figure 3.7 Photograph of a fabricated moisture FBG sensor with a PI coating ...

Figure 3.8 Schematic diagram of the packaged sensor probe with moisture and ...

Figure 3.9 Moisture installation inside a power transformer with a customize...

Figure 3.10 Distribution moisture measurement system based on FBGs. Source: ...

Figure 3.11 Geometry representation of the radiation loss of an evanescent w...

Figure 3.12 Evanescent field generation and distribution around the MNF.

Figure 3.13 Evanescent wave energy distribution diagram of MNF with differen...

Figure 3.14 The experimental setup for fabrication of a micro‐nano fiber by ...

Figure 3.15 The fabrication of a micro‐nano fiber by self‐modulated taper‐dr...

Figure 3.16 The implementation diagram of the fabrication of micro‐nano fibe...

Figure 3.17 Enlarged MNF images with different diameters.

Figure 3.18 Experimental setup to detect moisture content based on an evanes...

Figure 3.19 Fiber optic evanescent wave absorption sensor. Source: Modified ...

Figure 3.20 (a) Sensing coating wrapped around the fiber, (b) sensing at the...

Figure 3.21 Layout of an FBG‐FP sensor for simultaneous measurement of moist...

Figure 3.22 Combination of LPG and FPI.

Chapter 4

Figure 4.1 Installation schematic of an online DGA in a power transformer. S...

Figure 4.2 Illustration of an online monitoring device for oil‐immersed powe...

Figure 4.3 Typical headspace degassing/extraction unit.

Figure 4.4 Coordinates and fault zones in the Duval triangle method (DTM)....

Figure 4.5 Principal illustration of photoacoustic spectroscopy detection. S...

Figure 4.6 Principle of the photoacoustic spectroscopy technique.

Figure 4.7 Schematic of the QEPAS measurement system. Source: Modified from ...

Figure 4.8 Structural illustration of photoacoustic spectroscopy detection. ...

Figure 4.9 Typical structure and prototype apparatus based on PAS.

Figure 4.10 Absorption spectrum distribution of ethyne in wavelengths rangin...

Figure 4.11 Principle of the Beer–Lambert law.

Figure 4.12 Absorption spectrum distribution of H

2

.

Figure 4.13 Absorption spectrum distribution of CH

4

.

Figure 4.14 Absorption spectrum distribution of C

2

H

2

.

Figure 4.15 Absorption spectrum distribution of C

2

H

4

.

Figure 4.16 Absorption spectrum distribution of C

2

H

6

.

Figure 4.17 Absorption spectrum distribution of CO.

Figure 4.18 Absorption spectrum distribution of CO

2

.

Figure 4.19 Absorption spectrum distribution of H

2

O.

Figure 4.20 Typical result of gas chromatography.

Figure 4.21 Experimental setup based on Fourier transform infrared spectrosc...

Figure 4.22 Transmittance distribution of pure oil in 1 cm and 4 cm optical ...

Figure 4.23 Absorbance distribution of oil samples in the range of 1480–1640...

Figure 4.24 Absorption of acetylene in the gas phase and oil at wavelength o...

Figure 4.25 Fitting curves of peak area vs. acetylene concentration at a 1 c...

Figure 4.26 Absorption spectra of different acetylene oil samples at a 4 cm ...

Figure 4.27 Fitting curves of peak area vs. acetylene concentration at a 4 c...

Figure 4.28 Schematic diagram of an oil‐dissolved gas analyzer.

Figure 4.29 Identifying and correcting spectral baseline distortions for an ...

Figure 4.30 Schematic diagram of the FTIR‐PAS system.

Figure 4.31 Illustration of gas concentration measurements by a second harmo...

Figure 4.32 Illustration of methane concentration and the second harmonic wa...

Figure 4.33 Main hardware components in a typical TDLAS system.

Figure 4.34 Influence factors of a hydrocarbon gases detection system.

Figure 4.35 Schematic diagram of the absorption line selection.

Figure 4.36 Absorption wavelength distribution of four hydrocarbon gases....

Figure 4.37 Reflection spot pattern of a far‐end and near‐end mirrors.

Figure 4.38 Structure view of the specialized long‐path multi‐pass cell.

Figure 4.39 Comparison of optical coupler vs. optical switch.

Figure 4.40 System configuration of TDLAS for hydrocarbon gases in transform...

Figure 4.41 Procedures of TDLAS measurement.

Figure 4.42 Typical absorption spectrum of methane.

Figure 4.43 2f signals of methane at different concentrations.

Figure 4.44 2f signals of ethyne at different concentrations.

Figure 4.45 500 μL/L methane detection and fitting at different temperatures...

Figure 4.46 500 μL/L methane detection and fitting at different pressures....

Figure 4.47 Mechanical structure of a multi‐gas detection system in the fiel...

Figure 4.48 Typical online DGA equipment in the field based on the TDLAS tec...

Figure 4.49 Schematic diagram of the Raman scattering phenomenon.

Figure 4.50 Raman detection platform for dissolved fault gases in transforme...

Figure 4.51 Schematic diagram of the Raman detecting optical path. Source: M...

Figure 4.52 A fiber Bragg grating structure with a refractive index profile ...

Figure 4.53 Different layers of the FBG‐based hydrogen sensor.

Figure 4.54 FBG arrangement on the sampling tray.

Figure 4.55 Sensitivity test at different hydrogen concentrations in oil....

Figure 4.56 Comparison of SEM morphology between (a) a pure Pd film and (b) ...

Figure 4.57 FBG hydrogen sensor with a Pd/Ag composite film at 20 –80 °C....

Figure 4.58 The fitting curves of oil temperature vs. response time.

Figure 4.59 Simplified model of the FBG‐based hydrogen sensor.

Figure 4.60 Structure of the EFBG‐based hydrogen sensor.

Figure 4.61 Hydrogen detection with three different cladding diameters.

Figure 4.62 Wavelength shift of an FBG‐based hydrogen sensor in the repeatab...

Figure 4.63 Contrasting sensitivity test of standard FBG vs. etched FBG in t...

Figure 4.64 Fabrication arrangement of the side‐polished FBG.

Figure 4.65 Structure of the SP‐FBG hydrogen sensor in a lateral and cross‐s...

Figure 4.66 Simplified physical model of the SP‐FBG hydrogen sensor.

Figure 4.67 Relative bending strain vs. thickness of the Pd coating.

Figure 4.68 Experimental setup of dissolved hydrogen detection in transforme...

Figure 4.69 Sensitivity test results at a low hydrogen concentration in tran...

Figure 4.70 Error bars and standard deviations of wavelength shifts at low h...

Figure 4.71 Illustration of health diagnosis and dynamic prediction of oil‐i...

Chapter 5

Figure 5.1 PD detection based on different approaches.

Figure 5.2 Simplified model of an insulation defect prior to PD.

Figure 5.3 Mechanism of partial discharge ultrasonic signal generation.

Figure 5.4 The optical PD detection using different techniques.

Figure 5.5 FBG detection systems using a narrow line‐width laser diode.

Figure 5.6 FBG detection systems using a broadband light source (such as a l...

Figure 5.7 Illustration of a PS‐FBG wavelength characteristic.

Figure 5.8 The linear region comparison between normal FBG vs. PS‐FBG.

Figure 5.9 Schematic diagram of the PD detection platform based on a PS‐FBG ...

Figure 5.10 Strategy of temperature compensation‐based cross‐correlation alg...

Figure 5.11 PD location with several PS‐FBG sensors within an oil tank.

Figure 5.12 PD detection principle with two FBGs.

Figure 5.13 Experimental setup of PD detection using two FBGs.

Figure 5.14 Illustration of atypical Fabry–Perot interference structure and ...

Figure 5.15 Schematic diagram of a typical IFPI sensor structure.

Figure 5.16 FP cavity processed by laser micromachining technology.

Figure 5.17 FP cavity composed of an all‐fiber structure.

Figure 5.18 FP cavity fabrication process of an all‐fiber FPI based on an ai...

Figure 5.19 Typical structure of the Mach‐Zehnder interference system.

Figure 5.20 Typical structure of the Michelson interference system.

Figure 5.21 Principle detected by a Sagnac interference structure. Source: M...

Figure 5.22 Mach‐Zehnder interference is used to detect PD in transformer oi...

Figure 5.23 The fiber winding on the surface of electrical equipment. Source...

Figure 5.24 Schematic diagram of a sensing probe with skeleton. Source: Modi...

Figure 5.25 Sagnac interference structure to detect PD ultrasonic signals.

Figure 5.26 Experimental platform for ultrasonic detection of real PD. Sourc...

Figure 5.27 The actual PD signals received by the optical fiber sensing prob...

Figure 5.28 Typical Sagnac detection and simulation amplitudes at 46 and 80 ...

Figure 5.29 Variation trend of output loss with bending radius.

Figure 5.30 Planar radial winding method.

Figure 5.31 The effect of phase modulation on the output light intensity whe...

Figure 5.32 The demodulation principle of phase generation carriers.

Figure 5.33 A dual M‐Z interferometric fiber sensor based on the WDM. Source...

Figure 5.34 Optic fiber sensor of a dual Sagnac interference PD detection sy...

Figure 5.35 Principle and basic structure of space division multiplexing. So...

Figure 5.36 Principle and basic structure of time division multiplexing. Sou...

Figure 5.37 Principle and basic structure of wavelength division multiplexin...

Figure 5.38 The structure of sensors combined by Sagnac and M‐Z. Source: Mod...

Figure 5.39 The structure of sensors combined by FBG and Michelson. Source: ...

Figure 5.40 The structure of sensors combined by FBG and FPI. Source: Modifi...

Figure 5.41 PD detection system based on a Sagnac interferometer.

Figure 5.42 Possible PD detection based on a linear Sagnac interferometer.

Figure 5.43 Layout and installation of an optical time domain reflection tec...

Chapter 6

Figure 6.1 Equivalent circuit of the sweep frequency impedance method at a h...

Figure 6.2 Deformation detection in transformer windings with optical sensor...

Figure 6.3 Optical fiber arrangement in the transformer.

Figure 6.4 Schematic diagram of transformer vibration transmission and noise...

Figure 6.5 Optoelectronic setup of the fiber‐optic laser interferometer.

Figure 6.6 Optoelectronic setup for interferometric measurements inside the ...

Figure 6.7 Typical structure of an FBG vibration sensor.

Figure 6.8 FBG installation for vibration monitoring in a transformer.

Figure 6.9 Typical vibration detection point arrangement of a three‐phase tr...

Figure 6.10 Illustration of the Faraday magneto‐optic effect.

Figure 6.11 Structure and topology of an all‐fiber type of optical current t...

Figure 6.12 The birefringence phenomenon of the Pockels effect.

Figure 6.13 Basic structure of an all‐fiber type optical voltage transformer...

Figure 6.14 Schematic diagram of an integrated optical electric field sensor...

Figure 6.15 (a) Birefringence phenomenon in an isotropic material and (b) a ...

Figure 6.16 Electric field measurement in an insulation oil based on the Ker...

Figure 6.17 Various optical techniques for the measurement in power transfor...

Figure 6.18 Potential optical measurements applied for power transformers.

Guide

Cover Page

Title Page

Copyright

Foreword

Preface

Acknowledgments

About the Authors

Acronyms

List of Figures

List of Tables

Table of Contents

Begin Reading

Index

WILEY END USER LICENSE AGREEMENT

Pages

iv

ix

xi

xii

xiii

xv

xvii

xviii

xix

xx

xxi

xxii

xxiii

xxiv

xxv

xxvi

xxvii

xxviii

xxix

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

207

208

209

210

211

212

213

213

214

215

216

217

218

219

220

221

Optical Sensing in Power Transformers

Jun Jiang

Nanjing University of Aeronautics and Astronautics, Nanjing, China

Guoming Ma

North China Electric Power University, Beijing, China

Copyright

This edition first published 2021

© 2021 John Wiley & Sons Ltd

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

The right of Jun Jiang and Guoming Ma to be identified as the authors of this work has been asserted in accordance with law.

Registered Offices

John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA

John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK

Editorial Office

The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK

For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.

Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats.

Limit of Liability/Disclaimer of Warranty

In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of experimental reagents, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each chemical, piece of equipment, reagent, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

Library of Congress Cataloging‐in‐Publication data applied for

HB : 9781119765288

Cover Design: Wiley

Cover Image: © wolv/Getty Images

Foreword

I believe that the present book is the first book related to a promising optic‐based online monitoring for power transformers in the power grid.

Power transformers are essential equipment for power delivery, which directly influence the security and stability of the large electric network. Therefore, the transformer condition assessment and failure analysis are very important issues for the electric power utilities. There is a very complicated environment in the transformer, which is related to the Multiple Physical Field and its coupling, such as intense electric field, intense magnetic field, heat transfer field, oil flow field, and so on. The current sensing systems are mostly located on the outside of the transformer in order to prevent senses from electromagnetic, chemical, and heating effects, resulting in less physical fields for measuring, low sensitivity for signal acquisition, and low spatial resolution for fault location. It is believed that optical sensing, especially optic fiber sensors, has an advantage of passive, lightweight, small size, EMI immunity, and is able to work in environments with multiple physical fields and chemical corrosion in the transformer. Therefore, I believe that optical sensing technology will be promising technology for a power transformer, not only in an on‐line condition monitoring aspect but also in fault protection issues.

This book is aimed to comprehensively present the different cutting‐edge optical principles and methodologies adopted for online monitoring of power transformers and covers the basic principle, key points, possible installations, and some results. Although some optical techniques are currently still not mature enough for in‐situ applications in power transformers, the book tries to inspire new chances and possibilities. In addition, there are abundant first‐hand information, experience, and knowledge on the optical techniques applied in power transformers contributed by Dr. Jiang Jun and Dr. Ma Guoming in this book, which may make it more attractive to the readers.

I really hope this book will be interesting to the audience of scientific researchers, technical R&D staff, manufacturers, frontline engineers, postgraduate students, et al., and we encourage every reader to explore more new possibilities applied in power transformers.

August, 2020

Chengrong Li

Professor

North China Electric Power University

Preface

Transformers are one of the most important pieces of equipment in a power grid. Its health index can significantly impact both the reliability and functionality of the power grid. However, partial in‐service transformers worldwide have already reached or exceeded their design life expectancy. Thus, real‐time online monitoring and assessment have been prioritized on the agenda among utilities around the globe to allow for a timely maintenance action and to avoid any potential catastrophic failures. Many new detection tools are being investigated continuously by researchers and engineers in the field. In particular, with advances in optical engineering and communications technology, the last few decades have witnessed the emergence and development of a new generation of optical approaches for power apparatus condition monitoring. The inherent advantages of fibre optic sensors include lightweight, compatibility, passivity, low attenuation, low power, immunity to electromagnetic interference (EMI), high sensitivity, wide bandwidth, and environmental ruggedness. These advantages are utilized to compromise for its high cost and unfamiliarity to the consumer. Therefore, they have become commonly used and applied in high voltage applications.

This book presents the concepts and current industry practice of various popular condition monitoring techniques such as temperature measurement, moisture analysis, dissolved gas analysis, partial discharge, winding deformation, vibration analysis, voltage/current measurement, and electric field measurement. The book also provides fundamental knowledge of optical principles and some practical techniques for optical probes design, circuit topology, alternative schemes, and the comprehensive merits and drawbacks. Primarily, the book offers a comprehensive and valuable source of information for researchers, utility engineers, operators, and technicians. It reflects a solid understanding of strategic concepts to maintain assets, optimize planned replacements, and minimize the possibility of catastrophic failures. Finally, it offers advanced material for undergraduate and postgraduate research students, and advanced teaching in the emerging field of advanced sensors and electric engineering.

This book is organized into six chapters.

Chapter

1

gives an overview of power transformers in power grids, their typical structure, as well as an overview of oil‐immersed insulation systems. This chapter also provides a foundation for understanding condition monitoring of oil‐immersed power transformers to provide a basic outline of traditional techniques and assist the reader in understanding the necessity of novel sensing.

Chapter

2

focuses on temperature detection with optical techniques, alongside heat sourcing and transferring in power transformers. Optical fiber sensors are developed to detect

hot spot temperature

(

HST

) and prevent a “fever” of power transformers, with point measurement, quasi‐distributed measurement, and distribution measurement.

Chapter

3

primarily explains moisture measurements by optical sensors, with a comprehensive guideline for three types: FBG, evanescent wave and

Fabry–Perot

(

FP

)‐based moisture measurements. To build a reasonable and practical online moisture detection, the factors of inferencing the measurement are considered and the pros and cons of each optical technique are weighed respectively.

Chapter

4

presents fundamentals of

dissolved gas analysis

(

DGA

) and its requirements for online monitoring. It also shows the categorization of optical schemes for dissolved gas analysis as

photoacoustic spectrum

(

PAS

),

Fourier transform infrared spectrum

(

FTIR

),

tunable diode laser absorption spectrum

(

TDLAS

),

laser Raman spectroscopy

(

LRS

), and

fiber Bragg grating

(

FBG

). Finally, it provides a comparison between currently used optical fiber techniques.

Chapter

5

concentrates on

partial discharge

(

PD

) activities detection with optical techniques on the basis of the PD‐induced weak acoustic emission effect. Three main optical techniques, based on different principles, are analyzed for PD detection, namely FBG, FP, and dual‐beam interference topology. The sensitivity enhancement, merits, and drawbacks of these techniques are presented as well.

Chapter

6

provides the measurement of mechanical and electrical parameters on the basis of optical solutions, such as winding deformation, high voltage, large current, and contactless electric fields. It also highlights the current condition monitoring limitation with optical techniques and the importance of future research.

The research work presented in this book is supported and funded by the National Natural Science Foundation of China and shows collaborative work and projects from several power utilities in China over a period of about 10 years. The book aims to provide the state‐of‐the‐art knowledge related to optical solutions for condition monitoring and fault diagnosis of power transformers.

Optical fibers may seem irrelevant to power transformers at first glance; however, it is extremely beneficial to combine the interdisciplinary subjects. The authors hope it can be a “must have” reference book and an adequate reference for anyone working with condition monitoring of power transformers. Nevertheless, a continuing effort in the academic research and industrial work is still necessary to emphasize the long‐term reliability of the information provided and improve the precision of optical measurements, respectively. Therefore, interests, efforts, opinions, and collaborations from enthusiastic readers are highly appreciated, in order to offer potential feasible solutions and improve the optical presence in the power industry.

Acknowledgments

Many people have supported this work, directly or indirectly, throughout our involvement with the interdisciplinary research and manuscript preparation. We would like to acknowledge some of the key personnel without whose contributions this publication would never have reached this point.

The authors are indebted to Prof. Chengrong Li and Prof. Zhongdong Wang for their generosity to find time in the demanding schedule to offer the Foreword and valuable suggestions for this book.

Mr. Bendong Zhang and Miss Kai Wang at Nanjing University of Aeronautics and Astronautics have contributed directly in preparing the manuscript of this book, especially for their persistent support on the figure drawing and information collection. Their contributions are greatly appreciated. Special thanks go to Dr. Prem Ranjan, Ms. Abir Al abani and Mr. Sanad Elrishe from The University of Manchester for their proofreading of all the chapters.

Jun Jiang would like to express his most sincere thanks to Mrs. Miao Yu, Mr. Wenqing Lu, Mrs. Xiaoyan Wu, and their kids (Leo, Future, and Lucky), who are the strength, support, and inspiration behind each word. He also feels very grateful to the Man_Delta group members for their companionship during the preparation process and COVID‐19 quarantine period in Manchester, UK.

In addition, the authors would like to acknowledge some projects for providing the financial and infrastructural support necessary for these research and development works. This work is supported in part by National Natural Science Foundation of China under Grant Nos. 51677070, 51807088, 51977075, in part by Natural Science Foundation of Jiangsu Province under Grant No. BK20170786, in part by Beijing Natural Science Foundation under Grant No. 3182036, in part by the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources under Grant No. LAPS19010. The authors also gratefully acknowledge financial support from China Scholarship Council (No. 201906835029), Fok Ying‐Tong Education Foundation for Young Teachers in the Higher Education Institutions of China (No. 161053), Young Elite Scientists Sponsorship Program (No. CAST YESS20160004), and 2019 CAST Outstanding International Youths Exchange Program.

Lastly, the authors are grateful for the extensive help provided by Juliet Booker for her dedication, attention to detail, and efforts during the preparation of this book.

About the Authors

Jun Jiang is an Associate Professor with the Jiangsu Key Laboratory of New Energy Generation and Power Conversion, Nanjing University of Aeronautics and Astronautics, China. He was born in Anqing, China, in 1988. He received the BE degree in electrical engineering and automation from China Agricultural University (CAU) in 2011 and PhD degree in high voltage and electrical insulation from North China Electric Power University (NCEPU) in 2016. During 2019–2020, he worked as an Academic Visitor/Honorary Staff in the Department of Electrical and Electronic Engineering, School of Engineering, The University of Manchester, UK.

At present, he is an IEEE Senior Member, Cigre member, and also a representative for Cigre JWG D1/A2.77 (Liquid Tests for Electrical Equipment). He has published more than 60 peer‐reviewed papers including more than 40 journal articles. Also, more than 12 patents have been granted. He was granted the Young Researcher Award by International Symposium on High Voltage Engineering (ISH) and the Outstanding Reviewers Award by IET High Voltage.

His research interests are optical fiber sensing, condition monitoring of power apparatus, and more‐electric‐aircraft.

Guo‐ming Ma is a Professor with the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and School of Electrical and Electronic Engineering, North China Electric Power University. His research interest covers transient measurement, advanced optical sensing, and condition monitoring of power apparatus.

He is an Associate Editor of High Voltage published by IET, Senior Member of IEEE, and CSEE.

His research achievement was awarded a 1st Prize of the China Power Technology Progress Award. He was selected for the “Young Elite Scientists Sponsorship Program” by the China Association for Science and Technology, 2017. He was awarded the “Outstanding Young Electrical Engineering Researcher of China” by the Chinese Society for Electrical Engineering, 2017.

As a first‐author, co‐first author, or corresponding author, he has published more than 90 academic papers. He is co‐drafter of two CIGRE technical brochures and one IEEE international standards. Until now, he has been granted 20+ Chinese invention patents.

He received approximately ten fundings from China government‐related agencies, and over twenty research contracts from State Grid Cooperation of China and China Southern Power Grid.

Acronyms

A.U.

Arbitrary unit

AC

Alternating current

AE

Acoustic emission

AI

Artificial intelligence

ANSI

American National Standards Institute

AOCT

All‐fiber optical current transformer

AOVT

All‐fiber type optical voltage transformer

APD

Avalanche photodiode

ASTM

American Society for Testing and Materials

BDV

Breakdown voltage

B‐OTDA

Brillouin optical time‐domain analysis

B‐OTDR

Brillouin optical time‐domain reflectometry

BSO

Bismuth silicon oxide

CBM

Condition‐based maintenance

CNT

Carbon nanotube

CT

Current transducers

CW

Continuous wave

DAQ

Data acquisition

DC

Direct current

DCM

Differential cross‐multiplication

DGA

Dissolved gas analysis

DP

Degree of polymerization

DTM

Duval triangle method

DTS

Distributed temperature sensing

EFBG

Etched FBG

EFPI

Extrinsic Fabry–Perot interferometer

EM

Electromagnetic

EMI

Electromagnetic interference

ESA

Electrical spectrum analyzer

ESDD

Equivalent salt deposit density

FBG

Fiber Bragg grating

FDS

Frequency domain dielectric spectroscopy

FEA

Finite element analysis

FEP

Fluorinated ethylene propylene

FE‐SEM

Field emission scanning electron microscope

FET

Field effect transistor

FIB

Focused ion beam

FID

Flame ionization detectors

FLCEAS

Frequency‐locking cavity enhanced absorption spectroscopy

FOSs

Fiber optic sensors

FP

Fabry–Perot

FPI

Fabry–Perot interferometer

FRA

Frequency response analysis

FRM

Faraday rotating mirror

FTIR

Fourier transform infrared spectroscopy

FWHM

Full width at half maximum

GC

Gas chromatography

GIS

Gas insulated switchgear

GMM

Gaussian mixture model

HFCT

High frequency current transformer

HITRAN

High‐resolution transmission molecular absorption database

HST

Hottest spot temperature

HVDC

High voltage direct current

IEC

International Electrotechnical Commission

IEEE

Institute of Electrical and Electronic Engineers

IFFT

Inverse fast Fourier transform

IFPI

Intrinsic Fabry–Perot interferometer

IR

Infrared spectroscopy

ISAM

Ionic self‐assembly monolayer

KDP

Potassium dihydrogen phosphate

KFT

Karl–Fischer titration

LCSET

Lowest cold start energizing temperatures

LD

Laser diode

LED

Light emitting diode

LOD

Limitation‐of‐detection

LPGs

Long period gratings

LRS

Laser Raman spectroscopy

LTC

Load tap changer

MCU

Micro control unit

MEMS

Micro electro machining system

MFC

Mass flow controller

MIR

Mid‐infrared

MMI

Multimode interference

MNF

Micro/nano fiber

M‐Z

Mach–Zehnder

NDIR

Non‐dispersive infrared

NIR

Near‐infrared

NPs

Nanoparticles

OCT

Optical current transducer

OFAF

Oil forced air forced type

OFAN

Oil forced air natural type

OFGs

Optical fiber gratings

OFWF

Oil forced water forced

ONAF

Oil natural air forced type

ONAN

Oil natural air natural type

ONWF

Oil natural water forced

OSP

Optical sensor probe

OVT

Optical voltage transducers

PA

Peak area

PAS

Photoacoustic spectroscopy

Pd

Palladium

PD

Partial discharge

P

D

Photodiode/photodetector

PDC

Polarization depolarization current

PDIV

Inception voltage of partial discharge

PET

Polyethylene glycol ester

PGC

Phase generation carrier

PI

Polyimide

PID

Proportion integration differentiation

PM

Planned maintenance

PMMA

Polymethyl methacrylate

PNNL

Pacific Northwest National Laboratory

PPV

Peak‐to‐peak voltage

PRPD

Phase‐resolved partial discharge

PS‐FBG

Phase‐shifted FBG

PTFE

Polytetrafluoroethylene

PVA

Polyvinyl acrylate

PZT

Piezoelectric transducer

QCL

Quantum cascade laser

QEO

Quadratic electro‐optic

QEPAS

Quartz‐enhanced photoacoustic spectroscopy

QTF

Quartz tuning fork

RAM

Residual amplitude modulation

RH

Relative humidity

RI

Refractive index

R‐OTDR

Raman optical time‐domain reflectometry

RS

Raman spectroscopy

SDM

Space division multiplexing

SERS

Surface‐enhanced Raman scattering

SHM

Structural health monitoring

SMF

Single‐mode fiber

SNR

Signal‐to‐noise ratio

SP

Side‐polished

SP‐FBG

side‐polished FBG

TCD

Thermal conductivity detectors

TDCG

Total dissolved combustible gas

TDLAS

Tunable diode laser absorption spectrum

TDM

Time division multiplexing

TEC

Thermoelectric

TF

Time frequency

THC

Total hydrocarbons

TLS

Tunable laser source

TOF

Time‐of‐flight

TOT

Top oil temperature

UHF

Ultra‐high frequency

VT

Voltage transducers

WDM

Wavelength division multiplex

WMS

Wavelength modulation spectroscopy

Φ‐OTDR

Phase sensitive optical time‐domain reflectometry

List of Figures

Figure 1.1

Power transformers in a typical power grid/schematic drawing of a power system.

Figure 1.2

Typical structure of a large‐scale oil‐immersed power transformers.

Figure 1.3

Illustration of typical components of typical transformer oil. Source: Reprinted with permission from J. Jiang et al. [

3

]. © 2019, Elsevier.

Figure 1.4

Roles and properties of insulation oil in power transformer.

Figure 1.5

Time and cost analysis of condition‐based maintenance.

Figure 2.1

Typical losses in an AC power transformer.

Figure 2.2

Thermal equilibrium in a power transformer.

Figure 2.3

Process to calculate the temperature distribution using a coupling FEA model.

Figure 2.4

Typical fluorescence characteristic curve.

Figure 2.5

Typical design of single fiber fluorescent probe.

Figure 2.6

Measurement of temperature based on the optical fluorescence lifetime. Source: Reprinted by permission of Jin et al. [

6

]. © 2020, SPIE.

Figure 2.7

Connection illustration of multiple fluorescent temperature measurement system.

Figure 2.8

Schematic representation of FBG‐based temperature sensing and its WDM principle.

Figure 2.9

Schematic diagram of a typical FBG temperature sensor probe. Source: Reprinted by permission of Yi et al. [

13

]. © 2016, IEEE.

Figure 2.10

Possible locations of the optical FBG sensors.

Figure 2.11

Temperature online monitoring system scheme. Source: Modified from Zhang et al. [

17

].

Figure 2.12

Illustration of a multi‐point measurement based on FBGs.

Figure 2.13

Typical spontaneous scattering spectrum in an optical fiber. Reproduced from Chai et al. [

2

].

Figure 2.14

Schematic diagram of the Raman scattering phenomenon.

Figure 2.15

The topology and working principle of R‐OTDR. Source: Modified from Chai et al. [

2

].

Figure 2.16

Typical distributed sensing fiber based on the winding structure.

Figure 2.17

Transformer temperature monitoring system based on distributed optical fiber sensing. Source: Adapted from Yunpeng et al. [

8

].

Figure 2.18

The optical fiber winding composite model and the measurement system.

Figure 2.19

Optical temperature sensing techniques in a power transformer.

Figure 3.1

Molecule structure of cellulose consisting of glucose rings with unsaturated OH groups.

Figure 3.2

Water solubility in transformer oil is dependent on the temperature.

Figure 3.3

Quality standard of transformer oil with regard to moisture content.

Figure 3.4

Schematic structure of a parallel plate capacitive sensor. Source: Reprinted by permission from Islam et al. [

10

]. © 2020, IEEE.

Figure 3.5

Repeat units of a PI molecule and the possible sites for water. Source: Reprinted by permission of Melcher et al. [

17

].

Figure 3.6

FBG‐based sensors for humidity monitoring.

Figure 3.7

Photograph of a fabricated moisture FBG sensor with a PI coating and the packaged version.

Figure 3.8

Schematic diagram of the packaged sensor probe with moisture and temperature measurements.

Figure 3.9

Moisture installation inside a power transformer with a customized pressboard space.

Figure 3.10

Distribution moisture measurement system based on FBGs. Source: Modified from Ansari et al. [

13

].

Figure 3.11

Geometry representation of the radiation loss of an evanescent wave at a fiber bend.

Figure 3.12

Evanescent field generation and distribution around the MNF.

Figure 3.13

Evanescent wave energy distribution diagram of MNF with different diameters. (a) Evanescent wave energy distribution diagram of 800 nm MNF. (b) Evanescent wave energy distribution diagram of 3 μm MNF. (c) Evanescent wave energy distribution diagram of 5 μm MNF. (d) Evanescent wave energy distribution diagram of 10 μm MNF.

Figure 3.14

The experimental setup for fabrication of a micro‐nano fiber by the flame‐brushing technique.

Figure 3.15

The fabrication of a micro‐nano fiber by self‐modulated taper‐drawing technique.

Figure 3.16

The implementation diagram of the fabrication of micro‐nano fiber by direct drawing from bulk.

Figure 3.17

Enlarged MNF images with different diameters.

Figure 3.18

Experimental setup to detect moisture content based on an evanescent wave of MNF.

Figure 3.19

Fiber optic evanescent wave absorption sensor. Source: Modified from Holzki et al. [

35

].

Figure 3.20

(a) Sensing coating wrapped around the fiber, (b) sensing at the end face of the fiber, (c) hollow core fiber as the cavity, and (d) wavelength shifts of the sensor in different moisture contents. Sources: Alwi et al. [

22

]; Yeo et al. [

43

].

Figure 3.21

Layout of an FBG‐FP sensor for simultaneous measurement of moisture and temperature.

Figure 3.22

Combination of LPG and FPI.

Figure 4.1

Installation schematic of an online DGA in a power transformer. Source: Modified from Bustamante et al. [

2

].

Figure 4.2

Illustration of an online monitoring device for oil‐immersed power transformers.

Figure 4.3

Typical headspace degassing/extraction unit.

Figure 4.4

Coordinates and fault zones in the Duval triangle method (DTM). Source: Reprinted by permission of British Standards Institution (BSI) [

26

]. © 1999, BSI Standards.

Figure 4.5

Principal illustration of photoacoustic spectroscopy detection. Sources: Ma [

38

] and Yang et al. [

39

].

Figure 4.6

Principle of the photoacoustic spectroscopy technique.

Figure 4.7

Schematic of the QEPAS measurement system. Source: Modified from Ma [

38

].

Figure 4.8

Structural illustration of photoacoustic spectroscopy detection. Sources: Bakar et al. [

10

]; Skelly [

42

].

Figure 4.9

Typical structure and prototype apparatus based on PAS.

Figure 4.10

Absorption spectrum distribution of ethyne in wavelengths ranging from 1500 to 1550 nm.

Figure 4.11

Principle of the Beer–Lambert law.

Figure 4.12

Absorption spectrum distribution of H

2

.

Figure 4.13

Absorption spectrum distribution of CH

4

.

Figure 4.14

Absorption spectrum distribution of C

2

H

2

.

Figure 4.15

Absorption spectrum distribution of C

2

H

4

.

Figure 4.16

Absorption spectrum distribution of C

2

H

6

.

Figure 4.17

Absorption spectrum distribution of CO.

Figure 4.18

Absorption spectrum distribution of CO

2

.

Figure 4.19

Absorption spectrum distribution of H

2

O.

Figure 4.20

Typical result of gas chromatography. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.21

Experimental setup based on Fourier transform infrared spectroscopy. Source: Adapted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.22

Transmittance distribution of pure oil in 1 cm and 4 cm optical path lengths. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.23

Absorbance distribution of oil samples in the range of 1480–1640 nm. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.24

Absorption of acetylene in the gas phase and oil at wavelength of 1480–1640 nm. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.25

Fitting curves of peak area vs. acetylene concentration at a 1 cm optical path length. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.26

Absorption spectra of different acetylene oil samples at a 4 cm optical path.

Figure 4.27

Fitting curves of peak area vs. acetylene concentration at a 4 cm optical path length. Source: Reprinted with permission from Jiang et al. [

54

]. © 2019 Elsevier.

Figure 4.28

Schematic diagram of an oil‐dissolved gas analyzer.

Figure 4.29

Identifying and correcting spectral baseline distortions for an online gas analysis.

Figure 4.30

Schematic diagram of the FTIR‐PAS system.

Figure 4.31

Illustration of gas concentration measurements by a second harmonic wave. Source: Reprinted with permission from Jiang et al. [

62

]. © 2018 Institute of Electrical and Electronics Engineers.

Figure 4.32

Illustration of methane concentration and the second harmonic wave signal.

Figure 4.33

Main hardware components in a typical TDLAS system. Source: Reprinted with permission from Jiang et al. [

65

].

Figure 4.34

Influence factors of a hydrocarbon gases detection system. Source: Adapted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.35

Schematic diagram of the absorption line selection. Source: Adapted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.36

Absorption wavelength distribution of four hydrocarbon gases. Source: Adapted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.37

Reflection spot pattern of a far‐end and near‐end mirrors. Source: Reprinted with permission from Jiang et al. [

62

]. © 2018 Institute of Electrical and Electronics Engineers.

Figure 4.38

Structure view of the specialized long‐path multi‐pass cell. Source: Reprinted with permission from Jiang et al. [

65

].

Figure 4.39

Comparison of optical coupler vs. optical switch. Source: Reprinted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.40

System configuration of TDLAS for hydrocarbon gases in transformer oil.

Figure 4.41

Procedures of TDLAS measurement. Source: Reprinted with permission from Jiang et al. [

47

]. © 2016 Institute of Electrical and Electronics Engineers.

Figure 4.42

Typical absorption spectrum of methane. Source: Reprinted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.43

2f signals of methane at different concentrations. Source: Reprinted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.44

2f signals of ethyne at different concentrations. Source: Reprinted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.45

500 μL/L methane detection and fitting at different temperatures. Source: Reprinted with permission from Jiang et al. [

62

]. © 2018 Institute of Electrical and Electronics Engineers.

Figure 4.46

500 μL/L methane detection and fitting at different pressures. Source: Reprinted with permission from Jiang et al. [

62

]. © 2018 Institute of Electrical and Electronics Engineers.

Figure 4.47

Mechanical structure of a multi‐gas detection system in the field. Source: Reprinted with permission from Jiang et al. [

65

]. © 2019 Institute of Electrical and Electronics Engineers.

Figure 4.48

Typical online DGA equipment in the field based on the TDLAS technique. Source: Based on Jiang et al. [

62

].

Figure 4.49

Schematic diagram of the Raman scattering phenomenon.

Figure 4.50

Raman detection platform for dissolved fault gases in transformer oil.

Figure 4.51

Schematic diagram of the Raman detecting optical path. Source: Modified from Gu et al. [

73

].

Figure 4.52

A fiber Bragg grating structure with a refractive index profile and spectral response.

Figure 4.53

Different layers of the FBG‐based hydrogen sensor. Source: Reprinted with permission from Ma et al. [

87

]. © 2015 American Institute of Physics.

Figure 4.54

FBG arrangement on the sampling tray.

Figure 4.55

Sensitivity test at different hydrogen concentrations in oil. Source: Reprinted with permission from Ma et al. [

87

]. © 2015 American Institute of Physics.

Figure 4.56

Comparison of SEM morphology between (a) a pure Pd film and (b) a Pd/Ag film. Source: Reprinted with permission from Ma et al. [

87

].

Figure 4.57

FBG hydrogen sensor with a Pd/Ag composite film at 20 –80 °C. Source: Reprinted with permission from Ma et al. [

87

]. © 2015 American Institute of Physics.

Figure 4.58

The fitting curves of oil temperature vs. response time. Source: Reprinted with permission from Ma et al. [

87

]. © 2015 American Institute of Physics.

Figure 4.59

Simplified model of the FBG‐based hydrogen sensor. Source: Reprinted with permission from Jiang et al. [

91

]. © 2015 American Institute of Physics.

Figure 4.60

Structure of the EFBG‐based hydrogen sensor.

Figure 4.61

Hydrogen detection with three different cladding diameters. Source: Reprinted with permission from Jiang et al. [

91

]. © 2015 American Institute of Physics.

Figure 4.62

Wavelength shift of an FBG‐based hydrogen sensor in the repeatability test. Source: Reprinted with permission from Jiang et al. [

91

]. © 2015 American Institute of Physics.

Figure 4.63

Contrasting sensitivity test of standard FBG vs. etched FBG in transformer oil. Source: Reproduced with permission from Jiang et al. [

91

]. © 2015 American Institute of Physics.

Figure 4.64

Fabrication arrangement of the side‐polished FBG.

Figure 4.65

Structure of the SP‐FBG hydrogen sensor in a lateral and cross‐sectional view.

Figure 4.66

Simplified physical model of the SP‐FBG hydrogen sensor.

Figure 4.67

Relative bending strain vs. thickness of the Pd coating.

Figure 4.68

Experimental setup of dissolved hydrogen detection in transformer oil.

Figure 4.69

Sensitivity test results at a low hydrogen concentration in transformer oil. Source: Adapted with permission from Jiang et al. [

92

]. © 2015 Institute of Electrical and Electronics Engineers.

Figure 4.70

Error bars and standard deviations of wavelength shifts at low hydrogen concentrations. Source: Reprinted with permission from Jiang et al. [

92

]. © 2015 Institute of Electrical and Electronics Engineers.

Figure 4.71

Illustration of health diagnosis and dynamic prediction of oil‐immersed power transformers based on DGA. Source: Adapted with permission from Jiang et al. [

110

].

Figure 5.1

PD detection based on different approaches.

Figure 5.2

Simplified model of an insulation defect prior to PD.

Figure 5.3

Mechanism of partial discharge ultrasonic signal generation.

Figure 5.4

The optical PD detection using different techniques.

Figure 5.5

FBG detection systems using a narrow line‐width laser diode.

Figure 5.6

FBG detection systems using a broadband light source (such as a light emitting diode, LED).

Figure 5.7

Illustration of a PS‐FBG wavelength characteristic.

Figure 5.8

The linear region comparison between normal FBG vs. PS‐FBG.

Figure 5.9

Schematic diagram of the PD detection platform based on a PS‐FBG ultrasonic sensing system.

Figure 5.10

Strategy of temperature compensation‐based cross‐correlation algorithm.

Figure 5.11

PD location with several PS‐FBG sensors within an oil tank.

Figure 5.12

PD detection principle with two FBGs.

Figure 5.13

Experimental setup of PD detection using two FBGs. Source: Reprinted with permission from MDPI [

10

].

Figure 5.14

Illustration of atypical Fabry–Perot interference structure and the tropology. Source: Modified from Deng et al. [

26

].

Figure 5.15

Schematic diagram of a typical IFPI sensor structure.

Figure 5.16

FP cavity processed by laser micromachining technology.

Figure 5.17

FP cavity composed of an all‐fiber structure.

Figure 5.18

FP cavity fabrication process of an all‐fiber FPI based on an air bubble. Adapted from Yan et al. [

39

].

Figure 5.19

Typical structure of the Mach‐Zehnder interference system.

Figure 5.20

Typical structure of the Michelson interference system.

Figure 5.21

Principle detected by a Sagnac interference structure. Source: Modified from Cho et al. [

55

].

Figure 5.22

Mach‐Zehnder interference is used to detect PD in transformer oil.

Figure 5.23

The fiber winding on the surface of electrical equipment. Source: Modified from Zargari and Blackbum [

59

].

Figure 5.24

Schematic diagram of a sensing probe with skeleton. Source: Modified from Zhang et al. [

60

].

Figure 5.25

Sagnac interference structure to detect PD ultrasonic signals.

Figure 5.26

Experimental platform for ultrasonic detection of real PD. Source: Jiang et al. [

56

].

Figure 5.27

The actual PD signals received by the optical fiber sensing probe.

Figure 5.28

Typical Sagnac detection and simulation amplitudes at 46 and 80 kHz.

Figure 5.29

Variation trend of output loss with bending radius.

Figure 5.30

Planar radial winding method.

Figure 5.31

The effect of phase modulation on the output light intensity when the initial phase is arbitrary.

Figure 5.32

The demodulation principle of phase generation carriers.

Figure 5.33

A dual M‐Z interferometric fiber sensor based on the WDM. Source: Modified from Lamela et al. [

85

].

Figure 5.34

Optic fiber sensor of a dual Sagnac interference PD detection system. Source: Modified from Russell et al. [

86

].

Figure 5.35

Principle and basic structure of space division multiplexing. Source: Modified from Comanici et al. [

88

].

Figure 5.36

Principle and basic structure of time division multiplexing. Source: Modified from Wang et al. [

89

].

Figure 5.37

Principle and basic structure of wavelength division multiplexing.

Figure 5.38

The structure of sensors combined by Sagnac and M‐Z. Source: Modified from Wang et al. [

46

].

Figure 5.39

The structure of sensors combined by FBG and Michelson. Source: Modified from Srivastava et al. [

91

].

Figure 5.40

The structure of sensors combined by FBG and FPI. Source: Modified from Yin et al. 2013 [

98

].

Figure 5.41

PD detection system based on a Sagnac interferometer.

Figure 5.42

Possible PD detection based on a linear Sagnac interferometer.

Figure 5.43

Layout and installation of an optical time domain reflection technique.

Figure 6.1

Equivalent circuit of the sweep frequency impedance method at a high frequency band. Source: Adapted from Yong et al. [

3

].

Figure 6.2

Deformation detection in transformer windings with optical sensors. Source: Adapted with permission from Melo et al. [

7

].

Figure 6.3

Optical fiber arrangement in the transformer. Source: Adapted from Yuang [

10

].

Figure 6.4

Schematic diagram of transformer vibration transmission and noise radiation. Source: Adapted from Shengchang et al. [

14

].

Figure 6.5

Optoelectronic setup of the fiber‐optic laser interferometer. Source: Adapted from Garcia‐Souto et al. [

18

].

Figure 6.6

Optoelectronic setup for interferometric measurements inside the power transformer. Source: Adapted from Rivera et al. [

19

].

Figure 6.7

Typical structure of an FBG vibration sensor. Source: Adapted from Min et al. [

15

].

Figure 6.8

FBG installation for vibration monitoring in a transformer. Source: Adapted from Raghavan et al. [

20

].

Figure 6.9

Typical vibration detection point arrangement of a three‐phase transformer.

Figure 6.10

Illustration of the Faraday magneto‐optic effect.

Figure 6.11

Structure and topology of an all‐fiber type of optical current transformer. Source: Adapted from Silva et al. [

24

].

Figure 6.12

The birefringence phenomenon of the Pockels effect.

Figure 6.13