变压器局放信号传播特性及小波包熵阈值法去干扰的研究
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摘要
变压器局部放电在线监测是高电压绝缘检测与诊断领域研究的热点课题。由于实际产生于变压器内部的局部放电信号非常微弱，加上现场严重的电磁干扰，局部放电信号的在线获取困难很大。现有技术虽然取得了一定效果，但还不能满足工程应用的要求。
本文针对现存的问题，从局放信号的传播和干扰的抑制两方面研究了脉冲电流法用于变压器局部放电在线监测。
首先，以Saber为工具，建立了变压器绕组及其所联网络和设备的暂态模型，研究了局部放电信号在其中传播的频率特性。分析了绕组的外联网络、不同的监测点、低压绕组、中性点接地方式等对局放信号幅度、频谱的影响，为局部放电在线监测频带、监测点的选择以及局放的定位提出了具体的建议。同时，结合传播特性，研究了局部放电在线监测宽带微电流传感器，并就线圈匝数、杂散电容和负载电阻等对传感器通频带、灵敏度等性能参数的影响进行了分析。
首次提出用于抑制局部放电在线监测中周期性窄带干扰的小波包变换熵阈值法（ETM）。利用小波包变换的频域分割特性，将信号信息测度的香农熵作为局部放电信号的小波包变换树节点存在窄带干扰与否的判据，成功地去除了窄带干扰。大量的仿真数据、实验室实测数据以及现场实测数据处理结果表明，小波包变换熵阈值法抑制干扰能力强，无需事先确定干扰的分布，能够准确检测局部放电信号的相位信息，对于单一的放电类型，可以确定放电量的大小。另外，还研究了信号的采样率、局放脉冲的波形、衰减时间常数、时间间隔、基小波的选取、干扰的中心频率和数目、熵阈值以及信噪比对处理效果的影响。
基于小波包变换的非平稳信号消噪算法（WPM）已较为成熟，本文将其应用于局部放电在线监测，通过研究其对不同局放波形、采样率、噪声水平下的处理效果，首次提出了理想白噪声条件下提取局部放电信号的曲线，分析了各种因素对该算法下信号失真的影响。
本文所取得的结论对变压器局部放电在线监测系统的设计具有一定的指导意义，其中一些方法经实测数据的验证，可直接用于局部放电在线监测。
On-line PD monitoring of power transformer is presently the research hotspot in the area of high voltage insulation measurement and diagnosis. Due to the weakness of PD signals and bigness of interferences, the extraction of PD pulses faces many difficulties. The developed techniques, with some achievements, have not met the demand of engineering application yet.
Aiming at the present problems, this thesis studies the PD signal extraction of Pulse Current Method （PCM） in two directions: signal propagation and interference suppression.
Firstly, with software Saber, it sets up the transient models of transformer windings and bus-connected networks and studies the propagation of PD signals in the system. The influences of bus-connected networks, different monitoring points, low voltage windings and types of neutral point grounding on the frequency responses of PD signals are analyzed which give suggestions for the selection of monitoring band and monitoring points and PD localization. Combined with researches on propagation characteristics, the micro-current sensor for on-line PD monitoring is developed and the effects of coil number, stray capacitance and loading resistance on pass-band and sensitivity are also studied.
Based on Wavelet Packet Decomposition （WPD）, Entropy Threshold Method （ETM） has been put forward to reject the Discrete Spectrum Interference （DSI） in on-line PD monitoring. With the frequency division of WPD, ETM uses Shannon entropy as the criterion of determining whether or not DSI exist in certain WPD tree nodes and interference are suppressed successfully. Lots of simulation data, lab data and on-site data have indicated that ETM works with good efficiency, without pre-knowing of DSI information, extracts the phase of PD pulses accurately and can calibrate quantity of single type discharge. It also studies the influencing factors including sampling frequency, PD waveform, decline time, time intervals between PD pulses, mother wavelet, center frequency of interference, entropy threshold value and SNR.
In addition, it applies Wavelet Packet Method （WPM） for non-stationary signal de-noising in on-line PD monitoring and analyzes the processing results under different PD waveform, sampling frequency and noise level. Firstly, the curve of PD
pulse is presented on condition of ideal white noise. Signal distortion analysis has shown that the criterion of valuing de-noising capability should be waveform parameters of PD pulse rather than noise level.
Conclusions drew in this thesis can be used to guide the design of on-line monitoring system, some of which, tested by on-site data, can be directly applied in on-line PD monitoring of transformer.
本文针对现存的问题，从局放信号的传播和干扰的抑制两方面研究了脉冲电流法用于变压器局部放电在线监测。
首先，以Saber为工具，建立了变压器绕组及其所联网络和设备的暂态模型，研究了局部放电信号在其中传播的频率特性。分析了绕组的外联网络、不同的监测点、低压绕组、中性点接地方式等对局放信号幅度、频谱的影响，为局部放电在线监测频带、监测点的选择以及局放的定位提出了具体的建议。同时，结合传播特性，研究了局部放电在线监测宽带微电流传感器，并就线圈匝数、杂散电容和负载电阻等对传感器通频带、灵敏度等性能参数的影响进行了分析。
首次提出用于抑制局部放电在线监测中周期性窄带干扰的小波包变换熵阈值法（ETM）。利用小波包变换的频域分割特性，将信号信息测度的香农熵作为局部放电信号的小波包变换树节点存在窄带干扰与否的判据，成功地去除了窄带干扰。大量的仿真数据、实验室实测数据以及现场实测数据处理结果表明，小波包变换熵阈值法抑制干扰能力强，无需事先确定干扰的分布，能够准确检测局部放电信号的相位信息，对于单一的放电类型，可以确定放电量的大小。另外，还研究了信号的采样率、局放脉冲的波形、衰减时间常数、时间间隔、基小波的选取、干扰的中心频率和数目、熵阈值以及信噪比对处理效果的影响。
基于小波包变换的非平稳信号消噪算法（WPM）已较为成熟，本文将其应用于局部放电在线监测，通过研究其对不同局放波形、采样率、噪声水平下的处理效果，首次提出了理想白噪声条件下提取局部放电信号的曲线，分析了各种因素对该算法下信号失真的影响。
本文所取得的结论对变压器局部放电在线监测系统的设计具有一定的指导意义，其中一些方法经实测数据的验证，可直接用于局部放电在线监测。
On-line PD monitoring of power transformer is presently the research hotspot in the area of high voltage insulation measurement and diagnosis. Due to the weakness of PD signals and bigness of interferences, the extraction of PD pulses faces many difficulties. The developed techniques, with some achievements, have not met the demand of engineering application yet.
Aiming at the present problems, this thesis studies the PD signal extraction of Pulse Current Method （PCM） in two directions: signal propagation and interference suppression.
Firstly, with software Saber, it sets up the transient models of transformer windings and bus-connected networks and studies the propagation of PD signals in the system. The influences of bus-connected networks, different monitoring points, low voltage windings and types of neutral point grounding on the frequency responses of PD signals are analyzed which give suggestions for the selection of monitoring band and monitoring points and PD localization. Combined with researches on propagation characteristics, the micro-current sensor for on-line PD monitoring is developed and the effects of coil number, stray capacitance and loading resistance on pass-band and sensitivity are also studied.
Based on Wavelet Packet Decomposition （WPD）, Entropy Threshold Method （ETM） has been put forward to reject the Discrete Spectrum Interference （DSI） in on-line PD monitoring. With the frequency division of WPD, ETM uses Shannon entropy as the criterion of determining whether or not DSI exist in certain WPD tree nodes and interference are suppressed successfully. Lots of simulation data, lab data and on-site data have indicated that ETM works with good efficiency, without pre-knowing of DSI information, extracts the phase of PD pulses accurately and can calibrate quantity of single type discharge. It also studies the influencing factors including sampling frequency, PD waveform, decline time, time intervals between PD pulses, mother wavelet, center frequency of interference, entropy threshold value and SNR.
In addition, it applies Wavelet Packet Method （WPM） for non-stationary signal de-noising in on-line PD monitoring and analyzes the processing results under different PD waveform, sampling frequency and noise level. Firstly, the curve of PD
pulse is presented on condition of ideal white noise. Signal distortion analysis has shown that the criterion of valuing de-noising capability should be waveform parameters of PD pulse rather than noise level.
Conclusions drew in this thesis can be used to guide the design of on-line monitoring system, some of which, tested by on-site data, can be directly applied in on-line PD monitoring of transformer.
引文
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[4] 张鹏辉，于钦学，任文娥，局部放电在线窄带检测系统的研究，高电压技术，VOL.26, NO.1, February 2000 :24-26
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[6] G.C.Stone, H.G.Sedding, N.Fujimoto and J.M.Braun, Practical Implementation of Ultrawideband Partial Discharge Detectors, IEEE Trans. On Electrical insulation, VOL.27, No.1, February 1992: 70-81
[7] 黄盛洁，梅刚，陈春生等，变压器局部放电在线监测技术研究。高电压技术 1996. 22（4）39-41
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[3] 马卫平，董旭柱，王忠东，朱德恒，郑良华，王朔，大型变压器局部放电在线监测系统研究，中国电力，VOL.33, NO.4, April 2000: 35-37
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[5] Georges H. Vaillancourt, Ryszard Malewski and David Train, Comparison of Three Techniques of Partial Discharge Measurement in Power Transformers, IEEE Trans. On Power Apparatus and Systems, VOL.PAS-104, NO.4, April 1985: 900-909
[6] G.C.Stone, H.G.Sedding, N.Fujimoto and J.M.Braun, Practical Implementation of Ultrawideband Partial Discharge Detectors, IEEE Trans. On Electrical insulation, VOL.27, No.1, February 1992: 70-81
[7] 黄盛洁，梅刚，陈春生等，变压器局部放电在线监测技术研究。高电压技术 1996. 22（4）39-41
[8] V. Nagesh and B.I.Gururaj "Evaluation of Digital Filters for Rejepting Discrete Spectral Interference in On-site PD Measurements", IEEE Transactions on Electrical Insulation ,Vol.28 No.1, Februry 1993: 73-85
[9] 高宁，高文胜，李福祺，朱得恒，变压器局放在线监测中的现场干扰分析，高电压技术，VOL.26, NO.2, 4 2000:31-33
[10] R.E.James, B.T.Phung and Q.Su, Application of Digital Filtering Techniques to the Determination of Partial Discharge Location in Transformers, IEEE Trans. On Electrical Insulation, VOL.24, No.4, August 1989: 657-668
[11] Xuzhu Dong, Deheng Zhu, Changchang Wang, Kexiong Tan, Simulation of Transformer PD Pulse Propagation and Monitoring for a 500kV Substation, IEEE Trans. On Dielectrics and Electrical insulation, VOL.6, No.6, December 1999:803-813
[12] 罗兵，孙才新，顾乐观，王财胜，变压器局部放电在线监测的非磁性心棒式电流传感器的研究，电工技术学报，1995年第4期：30-35
[13] 吴广宁，马积勋等，大型电机局部放电在线监测用宽频电流传感器及应用的研究，西安交通大学学报，1996年第6期：8-13
[14] 张贤达，现代信号处理，北京：清华大学出版社，1995
[15] 王宏禹，非平稳随机信号分析与处理，北京：国防工业出版社，1999
[16] 王忠东, 在线监测局部放电中抗干扰技术的研究 [硕士学位论文] 北京:清华大学电机工程与应用电子系
[17] 谢尔.扎曼. 局部放电在线监测中抑制电磁干扰的自适应系统 [博士学位论文] 北京:清华大学电机工程与应用电子系
[18]. H.Bosi, M.Haitje ,Application of rogowski coils for partial discharge decoupling and noise suppression. Proc. of 5th 2sh ,1978mBraunschweig , No. 42.02
[19] R Malewski, etal. Insulation diagnostic system for HV power transformer in service.
IREQ.CIGRE, 12-01,1986
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