CVT故障快速辨识的实用化方法
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摘要
CVT故障率的升高给电网设备监测及事故抢修工作造成了严重影响。文中基于CVT在线监测数据提出了一种快速辨识CVT是否出现异常的小波实用化方法,解决了传统算法上CVT采集数据量大、辨识慢等问题。首先利用小波多分辨分析对CVT电压进行小波阈值去噪,结合CVT运行特点提出了去噪阈值函数的选择规律。接下来利用模极大值法重点研究了CVT击穿时各小波基函数辨识能力的优劣,利用小波三尺度重构的方法提取出CVT的异常波形并确定故障的位置信息。算例结果说明了该方法在辨识CVT故障信号的有效性和可行性。
The increase of the failure rate of CVT has impacted on equipment monitoring and accident repair work seriously.Based on the CVT online monitoring data,we proposed a wavelet practical method for quickly identifying the abnormality of CVT which solved the problems of large data acquisition and slow identification in traditional algorithms. Firstly,the wavelet multi-resolution analysis was adopted to de-noise voltage data,and the selection rules of de-noising threshold function were proposed combining with the characteristics of CVT operation. Next,the modular maxima method was adopted to evaluate each wavelet basis function under the breakdown of CVT. Then,the wavelet tri-scale reconstruction method was adopted to extract the abnormal waveform of CVT signal and determine the position information when the abnormality occurred. The results of the example showed the effectiveness and feasibility of this method on identifying CVT fault signals.
The increase of the failure rate of CVT has impacted on equipment monitoring and accident repair work seriously.Based on the CVT online monitoring data,we proposed a wavelet practical method for quickly identifying the abnormality of CVT which solved the problems of large data acquisition and slow identification in traditional algorithms. Firstly,the wavelet multi-resolution analysis was adopted to de-noise voltage data,and the selection rules of de-noising threshold function were proposed combining with the characteristics of CVT operation. Next,the modular maxima method was adopted to evaluate each wavelet basis function under the breakdown of CVT. Then,the wavelet tri-scale reconstruction method was adopted to extract the abnormal waveform of CVT signal and determine the position information when the abnormality occurred. The results of the example showed the effectiveness and feasibility of this method on identifying CVT fault signals.
引文
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[13]严志坚.一起500kV CVT电容分压器元件击穿故障的分析和处理[J].机电信息,2016,21:26-27.
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[15]Taswell C. The What,How,and Why of Wavelet Shrinkage Denoising.Computing in Science&Engineering,2000,2(3):12-19.
[16]Donoho D L,Johnstone I M,Kerkyacharian G,et al. Waveletshrinkage:Asymptopia[J]. Journal of the Royal Statistical Society,Series B,1995,57:301-369.
[17]Angrisani L,Daponte P,D'Apuzzo M,et al. A Measurement Method Based on the Wavelet Transform for Power Quality Analysis. IEEE Trans on Power Delivery,1998,13(4):990-998.
[18]田书,贾纯纯,马超.故障定位中小波基的选择研究[J].煤矿机械,2008,29(9):205-206.
[2]洪乐洲,吴贻志,李靖翔.电容式电压互感器二次电压异常分析处理[J].电力电容器与无功补偿,2012,33(3):73-76.Hong Lezhou,Wu Yizhi,Li Jingxiang,et al,Analysis and Treatment on Abnormal Secondary Voltage of Capacitor Voltage Transformers[J].Power Capacitor&Reactive Power Compensation,2012,33(3):73-76.
[3]刘胜军,霍春燕,何燕,等.一起220kV CVT二次电压偏高的分析处理[J].电力电容器与无功补偿,2013,34(4):69-74.Liu Shengjun,Huo Chunyan,He Yan,et al. Analysis and Treatment on Higher Secondary Voltage of One 220 k V CVT[J]. Power Capacitor&Reactive Power Compensation,2013,34(4):69-74.
[4]陈涛涛,陆金,许小飞.电容式电压互感器状态监测技术研究现状与发展[J].江苏电机工程,2016,35(5):63-66.Chen Taotao,Lu Jin,Xu Xiaofei. Current Status and Development of Condition Monitoring Technology for Capacitor Voltage Transformer[J].Jiangsu Electrical Engineering,2016,35(5):63-66.
[5]林浩,倪学峰,王岩,等.基于EMS数据的电容式电压互感器在线监测系统研究[J].电测与仪表,2015,52(4):1-6.Lin Hao,Ni Xuefeng,Wang Yan,et al. Research on on-line monitoring system of capacitor voltage transformer based on EMS data[J]. Electrical Measurement&Instrumentation,2015,52(4):1-6.
[6]刘建月,张志东,薛赵红,等.电容式电压互感器故障在线检定方法[J].电气技术,2015,16(5):124-127.
[7]付炜平,霍春燕. CVT早期故障监测方法[J].电力电容器与无功补偿,2009,30(2):29-31.
[8]周春雨.隔离开关操作CVT二次引起电压异常的分析[J].电力电容器与无功补偿,2008,29(5):54-57.
[9]卢峰超,刘红漫.利用电压Y值分析法诊断CVT早期故障[J].华北电力技术,2012,(2):40-44.
[10]费双波.小波去噪算法及小波硬件实现[D].北京:北京交通大学,2006.
[11]杨福生.小波变换的工程分析与应用[M].北京:科学出版社,1999:1-145.
[12]欧阳森,宋政湘,陈德桂.小波软阈值去噪技术在电能质量检测中的应用[J].电力系统自动化,2002,26(19):56-60.
[13]严志坚.一起500kV CVT电容分压器元件击穿故障的分析和处理[J].机电信息,2016,21:26-27.
[14]钟建军,宋健,由长喜,殷信桥.基于信噪比评价的阈值优选小波去噪法[J].清华大学学报(自然科学报),2014,54(2):260-262.
[15]Taswell C. The What,How,and Why of Wavelet Shrinkage Denoising.Computing in Science&Engineering,2000,2(3):12-19.
[16]Donoho D L,Johnstone I M,Kerkyacharian G,et al. Waveletshrinkage:Asymptopia[J]. Journal of the Royal Statistical Society,Series B,1995,57:301-369.
[17]Angrisani L,Daponte P,D'Apuzzo M,et al. A Measurement Method Based on the Wavelet Transform for Power Quality Analysis. IEEE Trans on Power Delivery,1998,13(4):990-998.
[18]田书,贾纯纯,马超.故障定位中小波基的选择研究[J].煤矿机械,2008,29(9):205-206.