220kV CVT故障的诊断及分析
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摘要
本文介绍了一起220 kV电容式电压互感器(CVT)的发热缺陷,通过红外测温确认其缺陷类型及部位,结合高压试验、返厂解体等分析缺陷原因,并验证其正确性。同时针对变电设备历史运行数据、所处环境等因素,提出基于融合特征的综合故障诊断体系,使其能更加准确、高效率地发现并诊断设备缺陷,保障设备安全运行。
In this paper, the defect of over heat in 220 kV capacitor voltage transformer(CVT) is introduced The defect type and location are confirm by the infrared thermometry, the reason of the defect is analyzed by way of high voltage test and disassembly at the factory and its correctness is verified. At the same time, in view of such factors as historical operation data and the situated environment etc. of the substation equipment the comprehensive fault diagnosis system is proposed based on the fusion features, so to keep it find and diagnose fault of the equipment more accurately and efficiently and assure safe operation of the equipment.
In this paper, the defect of over heat in 220 kV capacitor voltage transformer(CVT) is introduced The defect type and location are confirm by the infrared thermometry, the reason of the defect is analyzed by way of high voltage test and disassembly at the factory and its correctness is verified. At the same time, in view of such factors as historical operation data and the situated environment etc. of the substation equipment the comprehensive fault diagnosis system is proposed based on the fusion features, so to keep it find and diagnose fault of the equipment more accurately and efficiently and assure safe operation of the equipment.
引文
[1]房金兰.关于电容式电压互感器技术发展的探讨[J].电力电容器与无功补偿,2013,34(1):1-6.FANG Jinlan. Discussion on technical development of capacitor voltage transformers[J]. Power Capacitor&Reactive Power Compensation, 2013,34(1):1-6.
[2]电容式电压互感器:GB/T4703-2007[S]. 2007.Capacitor voltage transformers:GB/T 4703—2007[S]. 2007.
[3]互感器第5部分:电容式电压互感器补充技术要求:GB/T 20840. 5—2013[S]. 2013.Instrument transformers-Part 5:Add-itional requirements for capacitor voltage transformers:GB/T 20840. 5—2013[S].2013.
[4]带电设备红外诊断技术应用规范:DL/T 664-2016[S].2016.Application rules of infrated diagnosis for live electrical equipment:DL/T 664-2016[S]. 2016.
[4]张云,彭杰.基于红外检测的CVT缺陷分析[J].电力电容器与无功补偿,2017,38(3):116-120.ZHANG Yon, PENG Jie. Defect analysis of CVT based on infrared detection[J]. Power Capacitor&Reactive Power Compensation,2017,38(3):116-120.
[5]朱德恒,严璋,谭克雄,等.电气设备状态监测与故障诊断技术[M].北京:中国电力出版社,2009.
[6]戴钦来,吴冬文,王宇,等.一起500 kV CVT电磁单元故障分析[J].电力电容器与无功补偿,2017,38(5):77-81.DAI Qinlai, WU Dongwen, WANG Yu, et al. Analysis on electromagnetic unit fault of 500 kV CVT[J]. Power Capacitor&Reactive Power Compensation,2017,38(5):77-81.
[8]电力设备预防性试验规程:DL/T596—1996[S]. 1996.Rules of preventive tests for electric power equipment:DL/T596—1996[S]. 1996.
[9]张兴飞.两起CVT电磁单元过热缺陷的分析和处理[J].电力电容器与无功补偿,2018,39(2):44-48.ZHANG Xingfei. Analysis and processing on two overheat defects of capacitor voltage transformer electromagnetic unit[J].Power Capacitor and Reactive Power Compensation, 2018,39(2):44-48.
[10]乔立凤,高敬更,温定筠,等.电容式电压互感器二次电压异常分析处理[J].电子测量技术,2013,36(2):116-118.QIAO Lifeng, GAO Jinggeng, WEN Dingjun, et al. Analysis and treatment on abnormal secondary voltage of capacitor voltage transformer[J]. Electronic Measurement Technology,2013,36(2):116-118.
[11]李佳伟,吴聪,吴聪聪,等.500 kV电容式电压互感器电磁单元过热故障分析[J].湖北电力,2017,41(10):33-36.LI Jiawei, WU Cong, WU Congcong,et al. Analysis of overheating fault of electromagnetic unit of 500 kV capacitive voltage transformer[J]. Hubei Electric Power,2017,41(10):33-36.
[12]王绪,王伟,郭末凯,等.一起CVT故障的分析和对策[J].电力电容器与无功补偿,2014,35(1):90-94.WANG Xu, WANG Wei, GUO Mokai, et al. Analysis and countermeasures on CVT fault[J]. Power Capacitor&Reactive Power Compensation,2014,35(1):90-94.
[13]李爽.基于多特征融合和深度学习的图像分类算法[J].河南科技学院学报:自然科学版,2018,46(4):50-55.LI Shuang. Image classification algorithm based on multiple feature fusion and deep learning[J]. Journal of Henan Institute of Science and Technology:Natural Science Edition, 2018,46(4):50-55.
[14]黄冬梅,许琼琼,贺琪,等.融合多特征的深度学习标注方法[J].计算机工程与应用,2018,54(1):224228.HUANG Dongmei, XU Qiongqiong, HE Qi, et al. Multifeatures fusion for image autoannotation based on DBN model[J].Computer Engineering and Applications, 2018,54(1):224-228.
[15]李德峰,刘松涛.基于特征融合的图像目标显著性检测方法[J].半导体光电,2018,39(6):898-908.LI Defeng, LIU Songtao. Image target saliency detection method based on feature fusion[J]. Semiconductor Optoelectronics,2018,39(6):898-908.
[16]顾鑫,王海涛,汪凌峰,等.基于不确定性度量的多特征融合跟踪[J].自动化学报,2011,37(5):550-559.GU Xin, WANG Haitao, WANG Lingfeng,et al. Fusing multiple features for object tracking based on uncertainty measurement[J].Acta Automatica Sinica,2011,37(5):550-559.
[2]电容式电压互感器:GB/T4703-2007[S]. 2007.Capacitor voltage transformers:GB/T 4703—2007[S]. 2007.
[3]互感器第5部分:电容式电压互感器补充技术要求:GB/T 20840. 5—2013[S]. 2013.Instrument transformers-Part 5:Add-itional requirements for capacitor voltage transformers:GB/T 20840. 5—2013[S].2013.
[4]带电设备红外诊断技术应用规范:DL/T 664-2016[S].2016.Application rules of infrated diagnosis for live electrical equipment:DL/T 664-2016[S]. 2016.
[4]张云,彭杰.基于红外检测的CVT缺陷分析[J].电力电容器与无功补偿,2017,38(3):116-120.ZHANG Yon, PENG Jie. Defect analysis of CVT based on infrared detection[J]. Power Capacitor&Reactive Power Compensation,2017,38(3):116-120.
[5]朱德恒,严璋,谭克雄,等.电气设备状态监测与故障诊断技术[M].北京:中国电力出版社,2009.
[6]戴钦来,吴冬文,王宇,等.一起500 kV CVT电磁单元故障分析[J].电力电容器与无功补偿,2017,38(5):77-81.DAI Qinlai, WU Dongwen, WANG Yu, et al. Analysis on electromagnetic unit fault of 500 kV CVT[J]. Power Capacitor&Reactive Power Compensation,2017,38(5):77-81.
[8]电力设备预防性试验规程:DL/T596—1996[S]. 1996.Rules of preventive tests for electric power equipment:DL/T596—1996[S]. 1996.
[9]张兴飞.两起CVT电磁单元过热缺陷的分析和处理[J].电力电容器与无功补偿,2018,39(2):44-48.ZHANG Xingfei. Analysis and processing on two overheat defects of capacitor voltage transformer electromagnetic unit[J].Power Capacitor and Reactive Power Compensation, 2018,39(2):44-48.
[10]乔立凤,高敬更,温定筠,等.电容式电压互感器二次电压异常分析处理[J].电子测量技术,2013,36(2):116-118.QIAO Lifeng, GAO Jinggeng, WEN Dingjun, et al. Analysis and treatment on abnormal secondary voltage of capacitor voltage transformer[J]. Electronic Measurement Technology,2013,36(2):116-118.
[11]李佳伟,吴聪,吴聪聪,等.500 kV电容式电压互感器电磁单元过热故障分析[J].湖北电力,2017,41(10):33-36.LI Jiawei, WU Cong, WU Congcong,et al. Analysis of overheating fault of electromagnetic unit of 500 kV capacitive voltage transformer[J]. Hubei Electric Power,2017,41(10):33-36.
[12]王绪,王伟,郭末凯,等.一起CVT故障的分析和对策[J].电力电容器与无功补偿,2014,35(1):90-94.WANG Xu, WANG Wei, GUO Mokai, et al. Analysis and countermeasures on CVT fault[J]. Power Capacitor&Reactive Power Compensation,2014,35(1):90-94.
[13]李爽.基于多特征融合和深度学习的图像分类算法[J].河南科技学院学报:自然科学版,2018,46(4):50-55.LI Shuang. Image classification algorithm based on multiple feature fusion and deep learning[J]. Journal of Henan Institute of Science and Technology:Natural Science Edition, 2018,46(4):50-55.
[14]黄冬梅,许琼琼,贺琪,等.融合多特征的深度学习标注方法[J].计算机工程与应用,2018,54(1):224228.HUANG Dongmei, XU Qiongqiong, HE Qi, et al. Multifeatures fusion for image autoannotation based on DBN model[J].Computer Engineering and Applications, 2018,54(1):224-228.
[15]李德峰,刘松涛.基于特征融合的图像目标显著性检测方法[J].半导体光电,2018,39(6):898-908.LI Defeng, LIU Songtao. Image target saliency detection method based on feature fusion[J]. Semiconductor Optoelectronics,2018,39(6):898-908.
[16]顾鑫,王海涛,汪凌峰,等.基于不确定性度量的多特征融合跟踪[J].自动化学报,2011,37(5):550-559.GU Xin, WANG Haitao, WANG Lingfeng,et al. Fusing multiple features for object tracking based on uncertainty measurement[J].Acta Automatica Sinica,2011,37(5):550-559.