Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于OCSVM的气体绝缘组合电器故障检测

来源:电工电气发布时间:2020-05-13 15:13浏览次数:875
基于OCSVM的气体绝缘组合电器故障检测
 
高玉峰
(国网江苏省电力有限公司徐州供电分公司, 江苏 徐州 221005)
 
    摘 要:为了检测气体绝缘组合电器(GIS)故障,提出了一种基于单分类支持向量机(OCSVM)的设备故障检测方法。该方法以选取GIS金属外壳振动加速度以及气体压力作为状态监测量,为了解决设备振动幅值受负载变化影响的问题,提取外壳振动信号峭度因子,与气体压力共同作为状态特征量;利用GIS正常状态特征量数据训练OCSVM模型,得到设备故障检测器,并利用故障检测器检测当前状态特征变量的异常程度来实现设备故障的检测,现场实测数据分析结果验证了该方法的有效性。
    关键词:气体绝缘组合电器;单分类支持向量机;峭度因子;气体压力;故障检测
    中图分类号:TM595     文献标识码:B     文章编号:1007-3175(2020)05-0052-04
 
Fault Detection of Gas Insulated Switchgear Based on One Class Support Vector Mechine
 
GAO Yu-feng
(State Grid Jiangsu Electric Power Co., Ltd Xuzhou Power Supply Branch, Xuzhou 221005, China)
 
    Abstract: In order to detect the fault of Gas insulated switchgear, a fault detection method based on one class support vector machine (OCSVM) is proposed.In this method, the vibration acceleration and gas pressure of the GIS metal casing are selected as the state monitoring variables.In order to solve the problem that the vibration amplitude of GIS metal enclosure is affected by the load, the kurtosis of the metal enclosure vibration signal is extracted and the gas pressure is used as the state characteristic quantity.The OCSVM model is trained by using the GIS normal state feature data to obtain the equipment fault detector, and the fault detector is used to detect the abnormal degree of the current state characteristic variables to realize the detection of equipment faults.The results of field measurement data analysis verify the effectiveness of the method.
    Key words: gas insulated switchgear; one class support vector mechine; kurtosis; air pressure; fault detection
 
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