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文章摘要
CVT故障快速辨识的实用化方法
Partical method of fast identification on fault of CVT
Received:May 14, 2018  Revised:May 14, 2018
DOI:10.19753/j.issn1001-1390.2019.012.004
中文关键词: 电容式电压互感器  小波多分辨分析  阈值去噪  故障辨识  模极大值
英文关键词: CVT  Wavelet Multiresolution  Threshold Denoising  Fault Identification  Modulus Maxima。
基金项目:国家自然科学基金项目( 重点项目)
Author NameAffiliationE-mail
Wei Jiafu School of Electrical Engineering and Information,Sichuan University m13438332030@163.com 
Qiang Wenyuan School of Electrical Engineering and Information,Sichuan University 821129213@qq.com 
Liu Youbo* School of Electrical Engineering and Information,Sichuan University liuyoubo@scu.edu.cn 
刘向龙   
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中文摘要:
      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。该文基于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。算例结果说明了本方法在辨识CVT故障信号的有效性和可行性。
英文摘要:
      The increase in 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, we used wavelet multi-resolution analysis to denoise voltage data,and proposed the selection rules of denoising threshold function in combination with the characteristics of CVT operation. Next, used the modular maxima method to evaluate each wavelet basis function under the breakdown of CVT. Then extracted the abnormal waveform of CVT signal and determined the position information when the abnormality occurred using wavelet tri-scale reconstruction method. The results of the example showed the effectiveness and feasibility of this method.
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