基于光纤电流传感器的局部放电检测方法研究
|
摘要
局部放电在线检测可以及时反映电力设备绝缘老化情况,是状态监测和故障诊断的重要手段。但是,由于现场强烈的电磁干扰严重影响传感器的灵敏度和检测的可靠性,高性能的传感器研制始终是局放在线检测研究中的一个重要课题。光学检测方法抗干扰能力强,绝缘性能好,灵敏度高,对于局放在线检测的研究意义重大。
本文提出将根据Faraday磁光效应原理研制的光纤电流传感器应用于局放检测,以光信号为检测量,为局部放电光学检测方法奠定了基础。分析了不同类型光纤电流传感器的特点,利用琼斯矩阵法对光纤电流传感器的偏振光系统进行研究,给出了不同状态偏振光的归一化琼斯矢量,对本文涉及的光学器件推导了相应的Jones矩阵,最终建立了光纤电流传感器的数学模型。
研制出有效带宽为300 MHz的全光纤结构光纤电流传感器,设计了相关的信号处理电路;采用双螺线管结构提高传感器灵敏度,螺线管形状的通电导体和光路之间的相对位置关系发生变化不会影响检测结果;分析了它的频率响应特性、抗干扰特性和光路损耗特性,与传统光纤电流传感器相比,该检测系统频率响应范围宽,灵敏度高。当传感器采用全光纤闭合结构光路设计并满足安培环路定律时,其抗电磁干扰性能最优。
介绍了线性双折射特性和产生的各种原因;分析了线性双折射对于系统的影响,认为线性双折射是光纤电流传感器检测中影响系统测量误差的主要因素,随着线性双折射的增加,系统灵敏度下降,如果系统没有线性双折射,则其它误差源的影响将容易预测和处理,并探讨了消除线性双折射的可行措施。
建立了局部放电实验系统及尖板放电、板板放电、内部放电、沿面放电和悬浮放电五种典型局放模型,通过本文研制的光纤电流传感器采集了各种局部放电信号,实验结果说明在强干扰环境下与其他方法相比较,基于光纤电流传感器的局部放电检测具有抗干扰能力强、绝缘特性好和响应速度快等特点。
恰当地提取特征参数是进行局部放电进行模式识别的关键环节,将光纤电流传感器采集到的局部放电时域信号转换为三维时频谱图,全面表征了局放信号的时间分量、频率分量和放电能量的分布,提取的特征参数同时反映了原始信号的时频特征,各分量之间互不干扰,所以更加准确。
本文采用基于非线性理论的分形盒子维数和空缺率描述复杂的时频表面,提取出局部放电三维时频谱图的时频特征参数,以描述时频谱图峰值处的陡度和下降沿的变化趋势,简化了特征向量的维数。基于时频分析方法的分形理论和BP神经网络可有效识别不同类型的局部放电,证明光纤电流传感器可用于局部放电检测和故障诊断。
Partial discharge (PD) on-line detection can timely reflect the degradation degree of power apparatus, thus becoming a useful technique for condition monitoring and failure diagnosis. Because of high level electromagnetic interference, the development of high quality sensor is the key of PD on-line detection. Optical detection method has many advantages, such as great ability of anti-interference, excellent insulation property, high sensitivity, and is helpful to PD on-line detection.
On basis of Faraday Effect, optical-fiber current sensor (OCS) is used for PD detection in the first time. It will possibly set a foundation for optical method applied into PD detection. The characteristics of different types OCS were analyzed and research into polarized light system of OCS using Jones matrix method, then the mathematics model of OCS was set up at last.
Full-fiber OCS with effective band of 300 MHz and correlative circuit has been developed. Double constructer was adopted to enhance the sensitivity of system. Then its frequency-response property, anti-interference property and loss property have been analyzed in detail, from which the conclusion can be got that when the closed light path of OCS meet Ampere’s law, the sensor is supposed to have anti-interference feature.
The cause of linear birefringence and its property was analyzed. The effects of all the factors on system error are related to the linear birefringence, and the larger the linear birefringence is, the larger the effects of the factors are. Methods to eliminate linear birefringence were discussed.
PD test system and five models were set up. After picking classical PD signals with OCS, a comparison has been made between the optical method and other methods used in high level interference environment, and the result shows that PD detection using OCS has many merits such as great ability of anti-interference, high sensitivity and quick response.
Suitable extraction of characteristic parameters is vital for PD pattern recognition. Single PD pulse acquired with OCS has been transformed into 3-D time-frequency image. The characteristics were represented with parameters of frequency, time and energy. It has been proposed that direct extraction of 3-D images may be used for PD pattern recognition. Compared with the methods for extraction of characteristic only in time domain or frequency domain, 3-D images can instantaneously reflect the magnitudes of different frequency components and their features in time domain, but there is no interference among different frequency components, thus it is more accurate than other methods.
In order to extract the features of 3-D images, the fractal box-counting dimension and vacancy rate are adopted to characterize the complex time-frequency surface, which reflect the gradient at the magnitude and the variation trend at the trailing edge of time-frequency spectrum and can compress the dimensions of vector. The identification results using back propagation neural network (BPNN) and fractal theory based on time-frequency method demonstrates the effectiveness of OCS in PD detection.
本文提出将根据Faraday磁光效应原理研制的光纤电流传感器应用于局放检测,以光信号为检测量,为局部放电光学检测方法奠定了基础。分析了不同类型光纤电流传感器的特点,利用琼斯矩阵法对光纤电流传感器的偏振光系统进行研究,给出了不同状态偏振光的归一化琼斯矢量,对本文涉及的光学器件推导了相应的Jones矩阵,最终建立了光纤电流传感器的数学模型。
研制出有效带宽为300 MHz的全光纤结构光纤电流传感器,设计了相关的信号处理电路;采用双螺线管结构提高传感器灵敏度,螺线管形状的通电导体和光路之间的相对位置关系发生变化不会影响检测结果;分析了它的频率响应特性、抗干扰特性和光路损耗特性,与传统光纤电流传感器相比,该检测系统频率响应范围宽,灵敏度高。当传感器采用全光纤闭合结构光路设计并满足安培环路定律时,其抗电磁干扰性能最优。
介绍了线性双折射特性和产生的各种原因;分析了线性双折射对于系统的影响,认为线性双折射是光纤电流传感器检测中影响系统测量误差的主要因素,随着线性双折射的增加,系统灵敏度下降,如果系统没有线性双折射,则其它误差源的影响将容易预测和处理,并探讨了消除线性双折射的可行措施。
建立了局部放电实验系统及尖板放电、板板放电、内部放电、沿面放电和悬浮放电五种典型局放模型,通过本文研制的光纤电流传感器采集了各种局部放电信号,实验结果说明在强干扰环境下与其他方法相比较,基于光纤电流传感器的局部放电检测具有抗干扰能力强、绝缘特性好和响应速度快等特点。
恰当地提取特征参数是进行局部放电进行模式识别的关键环节,将光纤电流传感器采集到的局部放电时域信号转换为三维时频谱图,全面表征了局放信号的时间分量、频率分量和放电能量的分布,提取的特征参数同时反映了原始信号的时频特征,各分量之间互不干扰,所以更加准确。
本文采用基于非线性理论的分形盒子维数和空缺率描述复杂的时频表面,提取出局部放电三维时频谱图的时频特征参数,以描述时频谱图峰值处的陡度和下降沿的变化趋势,简化了特征向量的维数。基于时频分析方法的分形理论和BP神经网络可有效识别不同类型的局部放电,证明光纤电流传感器可用于局部放电检测和故障诊断。
Partial discharge (PD) on-line detection can timely reflect the degradation degree of power apparatus, thus becoming a useful technique for condition monitoring and failure diagnosis. Because of high level electromagnetic interference, the development of high quality sensor is the key of PD on-line detection. Optical detection method has many advantages, such as great ability of anti-interference, excellent insulation property, high sensitivity, and is helpful to PD on-line detection.
On basis of Faraday Effect, optical-fiber current sensor (OCS) is used for PD detection in the first time. It will possibly set a foundation for optical method applied into PD detection. The characteristics of different types OCS were analyzed and research into polarized light system of OCS using Jones matrix method, then the mathematics model of OCS was set up at last.
Full-fiber OCS with effective band of 300 MHz and correlative circuit has been developed. Double constructer was adopted to enhance the sensitivity of system. Then its frequency-response property, anti-interference property and loss property have been analyzed in detail, from which the conclusion can be got that when the closed light path of OCS meet Ampere’s law, the sensor is supposed to have anti-interference feature.
The cause of linear birefringence and its property was analyzed. The effects of all the factors on system error are related to the linear birefringence, and the larger the linear birefringence is, the larger the effects of the factors are. Methods to eliminate linear birefringence were discussed.
PD test system and five models were set up. After picking classical PD signals with OCS, a comparison has been made between the optical method and other methods used in high level interference environment, and the result shows that PD detection using OCS has many merits such as great ability of anti-interference, high sensitivity and quick response.
Suitable extraction of characteristic parameters is vital for PD pattern recognition. Single PD pulse acquired with OCS has been transformed into 3-D time-frequency image. The characteristics were represented with parameters of frequency, time and energy. It has been proposed that direct extraction of 3-D images may be used for PD pattern recognition. Compared with the methods for extraction of characteristic only in time domain or frequency domain, 3-D images can instantaneously reflect the magnitudes of different frequency components and their features in time domain, but there is no interference among different frequency components, thus it is more accurate than other methods.
In order to extract the features of 3-D images, the fractal box-counting dimension and vacancy rate are adopted to characterize the complex time-frequency surface, which reflect the gradient at the magnitude and the variation trend at the trailing edge of time-frequency spectrum and can compress the dimensions of vector. The identification results using back propagation neural network (BPNN) and fractal theory based on time-frequency method demonstrates the effectiveness of OCS in PD detection.
引文
[1]赵凯,陈丽娟,2005年全国电力可靠性统计分析[J],中国电力,2005,38(5):1-8
[2]朱德恒,谈克雄,电绝缘诊断技术[M],北京:中国电力出版社,1999
[3]严璋,电气绝缘在线检测技术[M],北京:中国电力出版社,1995
[4]Morshuis P H F. Degradation of solid dielectrics due to internal partial discharge: some thoughts on progress made and where to go now [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2005,12(5):905-913
[5]朱德恒,严璋,高电压绝缘[M],北京:清华大学出版社,1992
[6]Bartnikas R. Partial discharges their mechanism, detection and measurement [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2002, 9(5): 763-807
[7]王昌长,李福琪,高胜友,电力设备的在线监测与故障诊断[M],北京:清华大学出版社,2006
[8]Yamamoto O, Hayashi M, Uenosono C. Studies on corona in transformer oil by measurement of space charge [J]. IEEE Transactions on Electrical Insulation, 1985, 20(2): 453- 457
[9]吴广宁,吴欣延,大型发电机局部放电在线监测仪的研究[J],仪器仪表学报,1998,19(l):1-5
[10]姜磊,李福棋,谈克雄,发电机放电监测系统[J] ,电工电能新技术,1998,4:56-59
[11]董旭柱,固定式变压器在线监测系统[J],清华大学学报,1997,37(9):33-36
[12]李福祺,新型固定式变压器局部放电在线监测系统[J],清华大学学报,1999,39(7):5-8
[13]Kemp I J. Partial discharge plant-monitoring technology: present and future developments [J]. IEE Proceeding Science Measurement Technology, 1995, 142(1): 4-10
[14]IEC Standard 60270, Partial Discharge Measurement [S], 1996
[15]Birlasekaran S, Leong W H,Comparison of known PD signals with the developed and commercial HFCT sensors [J]. IEEE Transactions on Power Delivery, 2007, 22(3): 1581-1591
[16]Brosche T, hiller W, Fauser E, Pfeifer W. Novel characterization of PD signals by real-time measurement of pulse parameters [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1999, 6(1):51-59
[17]Hikita M, Okabe S, Murase H. Cross-equipment evaluation of partial discharge measurement and diagnosis techniques in electric power apparatus for transmission and distribution [J]. IEEE Transactions on Dielectrics and Electrical Insulation. 2008, 15(2): 505-518
[18]邱昌容,王乃庆,电工设备局部放电及其测试技术[M],北京:机械工业出版社,1994
[19]董其国,电力变压器故障与诊断[M],北京:中国电力出版社,2001
[20]Hamilton D J, Pearson J S. Classification of partial discharge sources in gas-insulated substations using novel preprocessing strategies [J]. IEE Proceedings-Science Measurement Technology, 1997, 144(1): 17-24
[21]Pearson J S, Farish O. Partial discharge diagnostics for gas insulated substations [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2 (5):893-905
[22]陈衡,侯善敬,电力设备红外诊断[M],北京:中国电力出版社,1999
[23]李智敏,超高频法检测GIS局部放电的研究[D],西安;西安交通大学,1999
[24]Judd M D,Yang L,Hunter L B B.Partial discharge monitoring for power transformer using UHF sensors Part 2: field experience [J]. IEEE Electrical Insulation Magazine,2005,21(3):5-13
[25]Ahmed N H,Srinivas N N. On-Line partial discharge detectionin cables [J],IEEE Transactions on Dielectrics and Electrical Insulation,1998,5( 2):181-188
[26]Judd M D, Farish O, Pearson J S. Power transformer monitoring using UHF sensors: installation and testing [C]. Conference Record of IEEE International Symposium on Electrical Insulation,2000:373-376
[27]Yang L, Judd M D,Bennoch C J. Denoising UHF signal for PD detection in transformers based on wavelet technique [C]. IEEE Conference on Electrical Insulation and Dielectric Phenomena, 2004:166-169
[28]王国利,郑毅,郝艳捧,李彦明,用于变压器局部放电检测的超高频传感器的初步研究[J],中国电机工程学报,2002,22(4):154-160
[29]王国利,单平,袁鹏,变压器局部放电超高频电磁波的传播特性[J],高电压技术,2002,28(12):26-28
[30]唐炬,侍海军,孙才新,用于GIS局部放电检测的内置超高频传感器特性研究[J],电工技术学报,2004,19(5):71-75
[31]唐志国,李成榕,黄兴泉,基于辐射电磁波检测的电力变压器局部放电定位研究[J],中国电机工程学报,2005, 26(3):96-101
[32]Sletbak J,Partial discharge measurements possibilities and limitations [C]. Proceedings of International Conference on Conduction and Breakdown in Solid Dielectrics,1992:145-149
[33]唐良,伍志荣,付锡年,运行中超高压变压器的故障在线监测[J],高电压技术,1996, 22(2):28-30
[34]Stone G,Partial Discharge-Part VII: Practical techniques for measuring PD in operating equipment [J]. IEEE Electrical Insulation Magazine, 1991, 7(4): 9-19
[35]王立欣,蔡惟铮,樊伟,王哲,高压变压器局部放电在线监测系统[J],哈尔滨工业大学学报,1998,30(3),64-67
[36]杨永明,电力变压器局部放电在线监测中干扰识别和抑制方法的研究[D],重庆;重庆大学,1999
[37]Pompili Mazzetti M C. Early stage of negative PD development in dielectric liquids [J]. IEEE Transactions on Dielectrics and Electrical Insulation ,1995,2(4):602-611
[38] Kopf U, Feser K. Rejection of narrow-band noise and repetitive pulse in on-site PD mearsurements [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2(3):433-447
[39]孙才新,罗兵,顾乐观,自适应数字滤波在局部放电在线监测信号处理中应用的研究[J],变压器, 1997, 34(7):19-24
[40]杨永明,孙才新,严欣平,抑制局部放电在线监测中周期性干扰的级联式IIR陷波滤波器的研究[J],电工技术学报,2000, 15 (5):75-78
[41]Allan D, Blundell M, Boyd K.New techniques for monitoring the insulation quality of in-service HV apparatus [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1992,27(3):578-585
[42]覃剑,陈祥训,郑建超,连续小波变换在检测强载波干扰中的局放信号的应用[J],电网技术,1998,22(3):41-45
[43]淡文刚,陈祥训,郑健超,采用小波分析与神经网络技术的局部放电统计识别方法[J],中国电机工程学报,2002,22(9):1-6
[44]Ma X D,Zhou C,Kemp I J. Investigation into the use of wavelet theory for partial discharge pulse extraction in electrically noisy environments [C]. International Conference on Dielectric Materials, Measurements and Applications, 2000:123-126
[45]程养春,李成榕,王伟.用傅立叶级数法消除局部放电检测中窄带干扰的研究[J].中国电机工程学报,2005,25(20):106-111
[46]李少慧,宁雅农,光纤传感器[M],武汉:华中理工大学出版社,1997
[47]Yoshimura N. Light emission from tracking discharges on organic insulation [J]. IEEE Transactions on Electrical Insulation,1984,19(2):149-156
[48]Mangeret R, Farenc J. Optical detection of partial discharges using fluorescent fiber [J]. IEEE Transactions on Electrical Insulation, 1991, 26 (4):783-789
[49]Miyamoto M,Hatakeyama Y. Partial discharge measurement with fluorescent optical fiber sensor [C]. Proceedings of the Asian Conference of Electrical Insulation Diagnosis,1999:216-220
[50]徐阳,喻明,曹晓珑,等,局部放电光脉冲测量法及与电测法的比较[J],高电压技术,2001,27(4):3-5
[51]魏念荣,张旭东,曹海翔,等,用荧光光纤技术检测局部放电信号传感器的研究[J],清华大学学报(自然科学版),2002,42(3):329-332
[52]MacAlpine M, Zhiqiang Z. Development of a fibre-optic sensor for partial discharges in oil-filledpower transformers [J]. Electric Power Systems Research,2002,63:27-36
[53]Xiaodong Wang, Baoqing Li, Harry T. Roman, Onofrio L. Russo, Ken Chin. Acousto-optical PD detection for transformers [J]. IEEE Transactions on Power Delivery, 2006,21(3):1068-1073
[54]Tian Y, Lewin P L. Partial discharge on-line monitoring for HV cablesystems using electrooptic modulators [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2004,11(5):861-869
[55]Tabor W J, Chen R S. Electromagnetic propagation through materials possessing both Faraday rotation and birefringence: experiments with ytterbium orthoferrite [J]. Applied Physics, 1969, 40(7):2760-2765
[56]Ulmer E A. High accuracy Faraday measurements [C]. International Conference on Optical Fiber Sensor, 1988, 21: 1- 4.
[57]Jaecklin A A, Lietz M. Elimination of disturbing birefringence effects on Faraday rotation [J]. Applied Optics, 1972, 11(3):617-621
[58]Cease T W, Driggans J G, Weikel S J. Optical voltage and current sensors used in a revenue metering system [J]. IEEE Transactions on Power Delivery, 1991, 12(4): 1422-1427
[59]Rose A H, Etzel S M, Rochford K B. Optical fiber current sensors in high electric field environments [J]. Lightwave Technology, 1999, 17(6):1042-1048
[60]Mafetone T D, Mcclelland T D. 345 kV substation optical current measurement system for revenue metering and protective relaying [J]. IEEE Transactions on Power Delivery, 1991, 6(4):1430-1437
[61]Takahashi M, Noda H, Terai K. Optical current transformer for gas insulated switchgear using silica optical fiber [J]. IEEE Transactions on Power Delivery, 1997, 12(4):1422-1427
[62]Kobayashi S, Horide A, Takagi I. Development and field test evaluation of optical current and voltage transformers for gas insulated switchgear [J]. IEEE Transactions on Power Delivery, 1992, 7(2):815-821
[63]Takahashi M, Noda H, Terai K. Optical current transformer for gas insulated switchgear using silica optical fiber [J].IEEE Transactions on Power Delivery, 1997, 12(4): 1422-1427
[64]易本顺,刘延兵,阮方,光学电流互感器现场运行性能分析[J],中国电机工程学报,1997,17(17):138-140
[65]李岩松,张国庆,郭志忠,提高光学电流互感器准确度的组合方法[J],电力系统自动化,2003,27(19):43-47
[66]沈悦,刘延冰,易本顺,实用化光学电流互感器[J],电子测量与仪器学报.1999, 10(2): 36-40
[67]李红斌,张明明,汪本进,等,光学电流互感器模拟输出的研究[J],传感器技术.2003, 6(11):21-23
[68]李芙英,纪昆,一种新型光电式电流互感器的设计[J],半导体光电,2002,(2):139-141
[69]Emerging Technologies Working Group, Fiber Optics Sensors Working Group. Optical current transducers for power systems: a review [J]. IEEE Transactions on Power Delivery, 1994,9(4): 1778-1788
[70]Macdougall T W, Lutz D R, Wandmacher R A. Development of a fiber optic current sensor for power systems [J]. IEEE Transactions on Power Delivery, 1992, 7(2): 848-852
[71]Ulmer E A. A high-accuracy optical current transducer for electric power systems [J]. IEEE Transactions on Power Deliverry, 1990, 5(2): 892-898
[72]郭凤珍,于长泰,光纤传感技术与应用[M],杭州:浙江大学出版社,1992
[73]Imamura M, Nakahara M, Tamura S. Output characteristics of field sensor used for optical current transformers applied to the flat-shape three-phase bus-bar [J]. IEEE Transactions on Magnetics, 1977, 33(5): 2403-2405
[74]魏光辉等,矩阵光学[M],北京:兵器工业出版社,1995
[75]石顺祥,刘继芳,孙艳玲,光的电磁理论:光波的传播与控制[M],西安:西安电子科技大学出版社,2006
[76]袁玉厂,冯丽爽,王夏霄,全光纤电流互感器检测系统的设计[J],光电工程,2006, 33(5): 94-98
[77]刘公强,磁光学[M],上海:上海科学技术出版社,2000
[78]高文胜,王猛,谈克雄,油纸绝缘中局部放电的典型波形及其频谱特性[J],中国电机工程学报,2002,22(2):1-5
[79]淡文刚,小波变换应用于大型电力变压器局部放电模式识别的研究[D],北京;中国电力科学研究院,2000
[80]淡文刚,陈祥训,郑健超,油中局部放电脉冲波形的测量与特性分析[J],电网技术,2000,24(6):37-40
[81]李锐华,谢恒堃,高乃奎,基于遗传编程的绝缘内部局部放电缺陷模式识别[J],中国电机工程学报,2003,23(8):105-109
[82]Satish L, Gururaj B I. Use of hidden markovmodel for partial discharge patern classification. IEEE Transactions on Dielectrics and Electrical Insulation [J],1993,28(2):172-182
[83]Zhenyuan W, Deheng Z, Kexiong T. PD monitor system for power generators [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1998,5(6):850-856
[84]Judd M D, Yang L, Hunter L B B. Partial discharge monitoring for power transformer using UHF sensors Part 2: field experience [J]. IEEE Electrical Insulation Magazine, 2005, 21(3): 5-13
[85]Cohen L,时-频分析:理论与应用[M],白居宪译,西安:西安交通大学出版社,1998.
[86]张贤达,保铮,非平稳信号的分析与处理[M],北京:国防工业出版社,1998
[87]李建平,小波分析与信号处理[M],重庆:重庆出版社,1997
[88]刘贵忠,邸双亮,小波分析及其应用[M],西安:西安电子科技大学出版社,1992
[89]Lalitha E M, Satish L. Wavelet analysis for classification of multi-source PD patterns [J], IEEE Transactions on Dielectrics and Electrical Insulation,2000,7(1):40-47
[90]Satish L,Nazneen B. Wavelet-based denoising of partial discharge signals buried in excessive noise and interference [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2003,10(2):354-367
[91]崔锦泰,小波分析导论[M],西安:西安交通大学出版社,1995
[92]李剑,孙才新,廖瑞金,用于局部放电图象识别的统计特征研究[J],中国电机工程学报,2002,22(9):104-107
[93]王晓蓉,杨敏中,董明,基于神经网络的局部放电脉冲特征参数选择方法[J],电工技术学报,2002,17(3):72-76
[94]李剑,孙才新,廖瑞金,用于局部放电图象识别的统计特征研究[J],中国电机工程学报,2002,22(9):104-107
[95]孙才新,李新,李俭,小波与分形理论的互补性及其在局部放电模式识别中的应用研究[J],中国电机工程学报,2001,21(12):73-76
[96]Lalitha E M, Satish L. Fractal image compressionf or classification of PD sources [J]. IEEE Transactions on Dielectrics and Electrical Insulatio,1998, 5(4):550-557
[97]Krivda A, Gulski E , Satish L, Zaengl W S. The use of fractal features for recognition of 3-D discharge patterns [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2(5):889-892
[98]Candela R, Mirelli G., Schifani R. PD recognition by means of statistical and fractal parameters and a neural network [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2000,7(l):87-94
[99]李剑,局部放电灰度图像识别特征提取与分形压缩方法的研究[D],重庆;重庆大学,2001
[100]孙才新,许高峰,唐炬,以盒维数和信息维数为识别特征量的GIS局部放电模式识别方法[J],中国电机工程学报,2005,25(3):100-104
[101]Satish L, Zaebg W S. Can Fractal features be used for recognizing 3-d partial discharge patterns? [J] , IEEE Transactions on Dielectrics and Electrical Insulation, 1995,2(3):352-359
[102]Mandelbrot B B. Fractal: Form, Chance and Dimension [M], Sen Francisco: Freeman, 1977.
[104]高凯,谈克雄,李福琪,基于散点集分形特征的局部放电模式识别研究[J].中国电机工程学报,2002,22(5):22-26
[105]Krivda A,Gulski E,Satish L. The use of fractal features for recognition of 3-D discharge patterns [J],IEEE Transactions on Dielectrics and Electrical Insulation, 1995, 2(5):889-892
[106]Takens F. Detecting Strange Attractors in Turbulence. Lecture Notes in Mathematics [J], Springer, 1981, 898, 366-381
[107]Sahoo N C, Salama M M A, Bartnikas R. Trends in partial discharge pattern classification: a survey [J], IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2):248-264.
[108]王晓蓉,变压器油纸绝缘局部放电脉冲的提取及放电特性研究[D],西安;西安交通大学,2001
[109]乐波,李俭,张晓红,等,基于指纹参量的环氧树脂绝缘多因子老化的实验研究[J],电工电能新技术,2001,(2):29-32
[110]Hans G K. Diagnosis of partial discharge signals usingneural networks and minimum distance classification [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1993,28(6):1018 -1024
[111]Hongetal T. PD classification by a modular neural networks based on task decomposition [J], IEEE Transactions on Dielectrics and Electrical Insulation, 1996, 3(2):112-114
[112]刘娜,高文胜,基于组合神经网络模型的电力变压器故障诊断方法[J],电工技术学报,2003,1 8(2):83-86
[113]Pal K, Mitra S. Multilayer perceptron, fuzzy sets, and classification [J], IEEE Transanctions on Neural Networks, 1992, 3(5): 683-697
[114]Hozumi N, Okamoto T, Imajo T. Discrimination of partial discharge patern using a neural network [J].IEEE Transactions on Electrical Insulation, 1992, 27(3): 550-556
[115]Mori H, Itou K, Vematsu H. An artificial neural net based method for predicting power system voltage harmonics [J].IEEE Transactions on Power Dilivery,1992, 7(1): 402-409
[116]王大忠,徐文,周泽存,模糊理论、专家系统及人工神经网络在变压器故障诊断中应用[J],中国电机工程学报,1996,16(5):349-355
[117]殷勤业,杨宗凯,模式识别与神经网络,机械工业出版社,1992
[118]Suzuki H, Endoh T. Pattern recognition of partial discharge in XLPE cables using a neural network [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1992, 27(3): 50-556
[2]朱德恒,谈克雄,电绝缘诊断技术[M],北京:中国电力出版社,1999
[3]严璋,电气绝缘在线检测技术[M],北京:中国电力出版社,1995
[4]Morshuis P H F. Degradation of solid dielectrics due to internal partial discharge: some thoughts on progress made and where to go now [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2005,12(5):905-913
[5]朱德恒,严璋,高电压绝缘[M],北京:清华大学出版社,1992
[6]Bartnikas R. Partial discharges their mechanism, detection and measurement [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 2002, 9(5): 763-807
[7]王昌长,李福琪,高胜友,电力设备的在线监测与故障诊断[M],北京:清华大学出版社,2006
[8]Yamamoto O, Hayashi M, Uenosono C. Studies on corona in transformer oil by measurement of space charge [J]. IEEE Transactions on Electrical Insulation, 1985, 20(2): 453- 457
[9]吴广宁,吴欣延,大型发电机局部放电在线监测仪的研究[J],仪器仪表学报,1998,19(l):1-5
[10]姜磊,李福棋,谈克雄,发电机放电监测系统[J] ,电工电能新技术,1998,4:56-59
[11]董旭柱,固定式变压器在线监测系统[J],清华大学学报,1997,37(9):33-36
[12]李福祺,新型固定式变压器局部放电在线监测系统[J],清华大学学报,1999,39(7):5-8
[13]Kemp I J. Partial discharge plant-monitoring technology: present and future developments [J]. IEE Proceeding Science Measurement Technology, 1995, 142(1): 4-10
[14]IEC Standard 60270, Partial Discharge Measurement [S], 1996
[15]Birlasekaran S, Leong W H,Comparison of known PD signals with the developed and commercial HFCT sensors [J]. IEEE Transactions on Power Delivery, 2007, 22(3): 1581-1591
[16]Brosche T, hiller W, Fauser E, Pfeifer W. Novel characterization of PD signals by real-time measurement of pulse parameters [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1999, 6(1):51-59
[17]Hikita M, Okabe S, Murase H. Cross-equipment evaluation of partial discharge measurement and diagnosis techniques in electric power apparatus for transmission and distribution [J]. IEEE Transactions on Dielectrics and Electrical Insulation. 2008, 15(2): 505-518
[18]邱昌容,王乃庆,电工设备局部放电及其测试技术[M],北京:机械工业出版社,1994
[19]董其国,电力变压器故障与诊断[M],北京:中国电力出版社,2001
[20]Hamilton D J, Pearson J S. Classification of partial discharge sources in gas-insulated substations using novel preprocessing strategies [J]. IEE Proceedings-Science Measurement Technology, 1997, 144(1): 17-24
[21]Pearson J S, Farish O. Partial discharge diagnostics for gas insulated substations [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2 (5):893-905
[22]陈衡,侯善敬,电力设备红外诊断[M],北京:中国电力出版社,1999
[23]李智敏,超高频法检测GIS局部放电的研究[D],西安;西安交通大学,1999
[24]Judd M D,Yang L,Hunter L B B.Partial discharge monitoring for power transformer using UHF sensors Part 2: field experience [J]. IEEE Electrical Insulation Magazine,2005,21(3):5-13
[25]Ahmed N H,Srinivas N N. On-Line partial discharge detectionin cables [J],IEEE Transactions on Dielectrics and Electrical Insulation,1998,5( 2):181-188
[26]Judd M D, Farish O, Pearson J S. Power transformer monitoring using UHF sensors: installation and testing [C]. Conference Record of IEEE International Symposium on Electrical Insulation,2000:373-376
[27]Yang L, Judd M D,Bennoch C J. Denoising UHF signal for PD detection in transformers based on wavelet technique [C]. IEEE Conference on Electrical Insulation and Dielectric Phenomena, 2004:166-169
[28]王国利,郑毅,郝艳捧,李彦明,用于变压器局部放电检测的超高频传感器的初步研究[J],中国电机工程学报,2002,22(4):154-160
[29]王国利,单平,袁鹏,变压器局部放电超高频电磁波的传播特性[J],高电压技术,2002,28(12):26-28
[30]唐炬,侍海军,孙才新,用于GIS局部放电检测的内置超高频传感器特性研究[J],电工技术学报,2004,19(5):71-75
[31]唐志国,李成榕,黄兴泉,基于辐射电磁波检测的电力变压器局部放电定位研究[J],中国电机工程学报,2005, 26(3):96-101
[32]Sletbak J,Partial discharge measurements possibilities and limitations [C]. Proceedings of International Conference on Conduction and Breakdown in Solid Dielectrics,1992:145-149
[33]唐良,伍志荣,付锡年,运行中超高压变压器的故障在线监测[J],高电压技术,1996, 22(2):28-30
[34]Stone G,Partial Discharge-Part VII: Practical techniques for measuring PD in operating equipment [J]. IEEE Electrical Insulation Magazine, 1991, 7(4): 9-19
[35]王立欣,蔡惟铮,樊伟,王哲,高压变压器局部放电在线监测系统[J],哈尔滨工业大学学报,1998,30(3),64-67
[36]杨永明,电力变压器局部放电在线监测中干扰识别和抑制方法的研究[D],重庆;重庆大学,1999
[37]Pompili Mazzetti M C. Early stage of negative PD development in dielectric liquids [J]. IEEE Transactions on Dielectrics and Electrical Insulation ,1995,2(4):602-611
[38] Kopf U, Feser K. Rejection of narrow-band noise and repetitive pulse in on-site PD mearsurements [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2(3):433-447
[39]孙才新,罗兵,顾乐观,自适应数字滤波在局部放电在线监测信号处理中应用的研究[J],变压器, 1997, 34(7):19-24
[40]杨永明,孙才新,严欣平,抑制局部放电在线监测中周期性干扰的级联式IIR陷波滤波器的研究[J],电工技术学报,2000, 15 (5):75-78
[41]Allan D, Blundell M, Boyd K.New techniques for monitoring the insulation quality of in-service HV apparatus [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1992,27(3):578-585
[42]覃剑,陈祥训,郑建超,连续小波变换在检测强载波干扰中的局放信号的应用[J],电网技术,1998,22(3):41-45
[43]淡文刚,陈祥训,郑健超,采用小波分析与神经网络技术的局部放电统计识别方法[J],中国电机工程学报,2002,22(9):1-6
[44]Ma X D,Zhou C,Kemp I J. Investigation into the use of wavelet theory for partial discharge pulse extraction in electrically noisy environments [C]. International Conference on Dielectric Materials, Measurements and Applications, 2000:123-126
[45]程养春,李成榕,王伟.用傅立叶级数法消除局部放电检测中窄带干扰的研究[J].中国电机工程学报,2005,25(20):106-111
[46]李少慧,宁雅农,光纤传感器[M],武汉:华中理工大学出版社,1997
[47]Yoshimura N. Light emission from tracking discharges on organic insulation [J]. IEEE Transactions on Electrical Insulation,1984,19(2):149-156
[48]Mangeret R, Farenc J. Optical detection of partial discharges using fluorescent fiber [J]. IEEE Transactions on Electrical Insulation, 1991, 26 (4):783-789
[49]Miyamoto M,Hatakeyama Y. Partial discharge measurement with fluorescent optical fiber sensor [C]. Proceedings of the Asian Conference of Electrical Insulation Diagnosis,1999:216-220
[50]徐阳,喻明,曹晓珑,等,局部放电光脉冲测量法及与电测法的比较[J],高电压技术,2001,27(4):3-5
[51]魏念荣,张旭东,曹海翔,等,用荧光光纤技术检测局部放电信号传感器的研究[J],清华大学学报(自然科学版),2002,42(3):329-332
[52]MacAlpine M, Zhiqiang Z. Development of a fibre-optic sensor for partial discharges in oil-filledpower transformers [J]. Electric Power Systems Research,2002,63:27-36
[53]Xiaodong Wang, Baoqing Li, Harry T. Roman, Onofrio L. Russo, Ken Chin. Acousto-optical PD detection for transformers [J]. IEEE Transactions on Power Delivery, 2006,21(3):1068-1073
[54]Tian Y, Lewin P L. Partial discharge on-line monitoring for HV cablesystems using electrooptic modulators [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2004,11(5):861-869
[55]Tabor W J, Chen R S. Electromagnetic propagation through materials possessing both Faraday rotation and birefringence: experiments with ytterbium orthoferrite [J]. Applied Physics, 1969, 40(7):2760-2765
[56]Ulmer E A. High accuracy Faraday measurements [C]. International Conference on Optical Fiber Sensor, 1988, 21: 1- 4.
[57]Jaecklin A A, Lietz M. Elimination of disturbing birefringence effects on Faraday rotation [J]. Applied Optics, 1972, 11(3):617-621
[58]Cease T W, Driggans J G, Weikel S J. Optical voltage and current sensors used in a revenue metering system [J]. IEEE Transactions on Power Delivery, 1991, 12(4): 1422-1427
[59]Rose A H, Etzel S M, Rochford K B. Optical fiber current sensors in high electric field environments [J]. Lightwave Technology, 1999, 17(6):1042-1048
[60]Mafetone T D, Mcclelland T D. 345 kV substation optical current measurement system for revenue metering and protective relaying [J]. IEEE Transactions on Power Delivery, 1991, 6(4):1430-1437
[61]Takahashi M, Noda H, Terai K. Optical current transformer for gas insulated switchgear using silica optical fiber [J]. IEEE Transactions on Power Delivery, 1997, 12(4):1422-1427
[62]Kobayashi S, Horide A, Takagi I. Development and field test evaluation of optical current and voltage transformers for gas insulated switchgear [J]. IEEE Transactions on Power Delivery, 1992, 7(2):815-821
[63]Takahashi M, Noda H, Terai K. Optical current transformer for gas insulated switchgear using silica optical fiber [J].IEEE Transactions on Power Delivery, 1997, 12(4): 1422-1427
[64]易本顺,刘延兵,阮方,光学电流互感器现场运行性能分析[J],中国电机工程学报,1997,17(17):138-140
[65]李岩松,张国庆,郭志忠,提高光学电流互感器准确度的组合方法[J],电力系统自动化,2003,27(19):43-47
[66]沈悦,刘延冰,易本顺,实用化光学电流互感器[J],电子测量与仪器学报.1999, 10(2): 36-40
[67]李红斌,张明明,汪本进,等,光学电流互感器模拟输出的研究[J],传感器技术.2003, 6(11):21-23
[68]李芙英,纪昆,一种新型光电式电流互感器的设计[J],半导体光电,2002,(2):139-141
[69]Emerging Technologies Working Group, Fiber Optics Sensors Working Group. Optical current transducers for power systems: a review [J]. IEEE Transactions on Power Delivery, 1994,9(4): 1778-1788
[70]Macdougall T W, Lutz D R, Wandmacher R A. Development of a fiber optic current sensor for power systems [J]. IEEE Transactions on Power Delivery, 1992, 7(2): 848-852
[71]Ulmer E A. A high-accuracy optical current transducer for electric power systems [J]. IEEE Transactions on Power Deliverry, 1990, 5(2): 892-898
[72]郭凤珍,于长泰,光纤传感技术与应用[M],杭州:浙江大学出版社,1992
[73]Imamura M, Nakahara M, Tamura S. Output characteristics of field sensor used for optical current transformers applied to the flat-shape three-phase bus-bar [J]. IEEE Transactions on Magnetics, 1977, 33(5): 2403-2405
[74]魏光辉等,矩阵光学[M],北京:兵器工业出版社,1995
[75]石顺祥,刘继芳,孙艳玲,光的电磁理论:光波的传播与控制[M],西安:西安电子科技大学出版社,2006
[76]袁玉厂,冯丽爽,王夏霄,全光纤电流互感器检测系统的设计[J],光电工程,2006, 33(5): 94-98
[77]刘公强,磁光学[M],上海:上海科学技术出版社,2000
[78]高文胜,王猛,谈克雄,油纸绝缘中局部放电的典型波形及其频谱特性[J],中国电机工程学报,2002,22(2):1-5
[79]淡文刚,小波变换应用于大型电力变压器局部放电模式识别的研究[D],北京;中国电力科学研究院,2000
[80]淡文刚,陈祥训,郑健超,油中局部放电脉冲波形的测量与特性分析[J],电网技术,2000,24(6):37-40
[81]李锐华,谢恒堃,高乃奎,基于遗传编程的绝缘内部局部放电缺陷模式识别[J],中国电机工程学报,2003,23(8):105-109
[82]Satish L, Gururaj B I. Use of hidden markovmodel for partial discharge patern classification. IEEE Transactions on Dielectrics and Electrical Insulation [J],1993,28(2):172-182
[83]Zhenyuan W, Deheng Z, Kexiong T. PD monitor system for power generators [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1998,5(6):850-856
[84]Judd M D, Yang L, Hunter L B B. Partial discharge monitoring for power transformer using UHF sensors Part 2: field experience [J]. IEEE Electrical Insulation Magazine, 2005, 21(3): 5-13
[85]Cohen L,时-频分析:理论与应用[M],白居宪译,西安:西安交通大学出版社,1998.
[86]张贤达,保铮,非平稳信号的分析与处理[M],北京:国防工业出版社,1998
[87]李建平,小波分析与信号处理[M],重庆:重庆出版社,1997
[88]刘贵忠,邸双亮,小波分析及其应用[M],西安:西安电子科技大学出版社,1992
[89]Lalitha E M, Satish L. Wavelet analysis for classification of multi-source PD patterns [J], IEEE Transactions on Dielectrics and Electrical Insulation,2000,7(1):40-47
[90]Satish L,Nazneen B. Wavelet-based denoising of partial discharge signals buried in excessive noise and interference [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2003,10(2):354-367
[91]崔锦泰,小波分析导论[M],西安:西安交通大学出版社,1995
[92]李剑,孙才新,廖瑞金,用于局部放电图象识别的统计特征研究[J],中国电机工程学报,2002,22(9):104-107
[93]王晓蓉,杨敏中,董明,基于神经网络的局部放电脉冲特征参数选择方法[J],电工技术学报,2002,17(3):72-76
[94]李剑,孙才新,廖瑞金,用于局部放电图象识别的统计特征研究[J],中国电机工程学报,2002,22(9):104-107
[95]孙才新,李新,李俭,小波与分形理论的互补性及其在局部放电模式识别中的应用研究[J],中国电机工程学报,2001,21(12):73-76
[96]Lalitha E M, Satish L. Fractal image compressionf or classification of PD sources [J]. IEEE Transactions on Dielectrics and Electrical Insulatio,1998, 5(4):550-557
[97]Krivda A, Gulski E , Satish L, Zaengl W S. The use of fractal features for recognition of 3-D discharge patterns [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1995,2(5):889-892
[98]Candela R, Mirelli G., Schifani R. PD recognition by means of statistical and fractal parameters and a neural network [J]. IEEE Transactions on Dielectrics and Electrical Insulation,2000,7(l):87-94
[99]李剑,局部放电灰度图像识别特征提取与分形压缩方法的研究[D],重庆;重庆大学,2001
[100]孙才新,许高峰,唐炬,以盒维数和信息维数为识别特征量的GIS局部放电模式识别方法[J],中国电机工程学报,2005,25(3):100-104
[101]Satish L, Zaebg W S. Can Fractal features be used for recognizing 3-d partial discharge patterns? [J] , IEEE Transactions on Dielectrics and Electrical Insulation, 1995,2(3):352-359
[102]Mandelbrot B B. Fractal: Form, Chance and Dimension [M], Sen Francisco: Freeman, 1977.
[104]高凯,谈克雄,李福琪,基于散点集分形特征的局部放电模式识别研究[J].中国电机工程学报,2002,22(5):22-26
[105]Krivda A,Gulski E,Satish L. The use of fractal features for recognition of 3-D discharge patterns [J],IEEE Transactions on Dielectrics and Electrical Insulation, 1995, 2(5):889-892
[106]Takens F. Detecting Strange Attractors in Turbulence. Lecture Notes in Mathematics [J], Springer, 1981, 898, 366-381
[107]Sahoo N C, Salama M M A, Bartnikas R. Trends in partial discharge pattern classification: a survey [J], IEEE Transactions on Dielectrics and Electrical Insulation, 2005, 12(2):248-264.
[108]王晓蓉,变压器油纸绝缘局部放电脉冲的提取及放电特性研究[D],西安;西安交通大学,2001
[109]乐波,李俭,张晓红,等,基于指纹参量的环氧树脂绝缘多因子老化的实验研究[J],电工电能新技术,2001,(2):29-32
[110]Hans G K. Diagnosis of partial discharge signals usingneural networks and minimum distance classification [J]. IEEE Transactions on Dielectrics and Electrical Insulation,1993,28(6):1018 -1024
[111]Hongetal T. PD classification by a modular neural networks based on task decomposition [J], IEEE Transactions on Dielectrics and Electrical Insulation, 1996, 3(2):112-114
[112]刘娜,高文胜,基于组合神经网络模型的电力变压器故障诊断方法[J],电工技术学报,2003,1 8(2):83-86
[113]Pal K, Mitra S. Multilayer perceptron, fuzzy sets, and classification [J], IEEE Transanctions on Neural Networks, 1992, 3(5): 683-697
[114]Hozumi N, Okamoto T, Imajo T. Discrimination of partial discharge patern using a neural network [J].IEEE Transactions on Electrical Insulation, 1992, 27(3): 550-556
[115]Mori H, Itou K, Vematsu H. An artificial neural net based method for predicting power system voltage harmonics [J].IEEE Transactions on Power Dilivery,1992, 7(1): 402-409
[116]王大忠,徐文,周泽存,模糊理论、专家系统及人工神经网络在变压器故障诊断中应用[J],中国电机工程学报,1996,16(5):349-355
[117]殷勤业,杨宗凯,模式识别与神经网络,机械工业出版社,1992
[118]Suzuki H, Endoh T. Pattern recognition of partial discharge in XLPE cables using a neural network [J]. IEEE Transactions on Dielectrics and Electrical Insulation, 1992, 27(3): 50-556