| 引用本文: | 姚海燕,张静,留毅,等.基于多尺度小波判据和时频特征关联的电缆早期故障
检测和识别方法[J].电力系统保护与控制,2015,43(9):115-123.[点击复制] |
| YAO Haiyan,ZHANG Jing,LIU Yi,et al.Method of cable incipient faults detection and identification based on multi-scale waveletcriterions and time-frequency feature association[J].Power System Protection and Control,2015,43(9):115-123[点击复制] |
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| 基于多尺度小波判据和时频特征关联的电缆早期故障
检测和识别方法 |
| 姚海燕,张静,留毅,潘姝,徐贝,李题印,周念成 |
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| (国网浙江杭州市余杭区供电公司，浙江 杭州 311100;输配电装备及系统安全与新技术国家
重点实验室，重庆 400044;国网资阳供电公司，四川 资阳 641300) |
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| 摘要: |
| 电力电缆早期故障主要为单相短路接地故障，为避免其发展成永久性故障，需要对电缆早期故障进行检测和识别。通过对比不同扰动源引起电缆过流的各相电流特性，利用多尺度小波变换提取电缆早期故障电流的特征量，以故障电流的高频细节系数、低频近似系数和模极大值组成复合判据，检测电缆过流的暂态过程。构建电缆早期故障的时频特征向量，利用灰色关联分析得到待测故障电流与标准电缆早期故障电流的关联度，以识别电缆早期故障。最后，利用PSCAD/EMTDC构建电缆线路模型，通过仿真分析验证了该方法的正确性。 |
| 关键词: 电力电缆 早期故障 小波变换 模极大值 灰色关联分析 |
| DOI：10.7667/j.issn.1674-3415.2015.09.018 |
| 投稿时间：2014-08-04修订日期：2014-11-26 |
| 基金项目:输配电装备及系统安全与新技术国家重点实验室自主研究项目（2007DA10512711209)；国家自然科学基金资助项目（51277184） |
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| Method of cable incipient faults detection and identification based on multi-scale waveletcriterions and time-frequency feature association |
| YAO Haiyan,ZHANG Jing,LIU Yi,PAN Shu,XU Bei,LI Tiyin,ZHOU Niancheng |
| (State Grid Zhejiang Hangzhou Yuhang Power Supply Company, Hangzhou 311100, China;State Key Laboratory
of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China;Ziyang Power Supply Bureau, Ziyang 641300, China) |
| Abstract: |
| Main power cable incipient faults are single phase short circuits with short duration and little effect on system operation, so the detection of cable incipient faults is needed to avoid them develop into permanent faults. The phase current characteristics of cable current caused by different disturbances are compared and the incipient faults current characteristic quantities are extracted by multi-scale wavelet transform, and fault current high frequency detail coefficients, low frequency approximation coefficients and the maximum module are taken as compound criterions to detect the transient process of cable over-currents. The time-frequency eigenvectors of cable incipient faults are created and the gray correlation analysis is used to obtain the relevancy of fault currents between fault currents of under-test and standard cable incipient faults in order to identify the incipient faults. At last, the cable line model is built in PSCAD/EMTDC, and the correction of the proposed method is verified by simulation analysis. |
| Key words: power cable incipient faults wavelet transform maximum module gray correlation analysis |
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