摘要详情
713 / 2022-03-31 17:20:47
A Method for Identifying and Locating Cable Faults Based on SVM and Impedance Spectroscopy
Impedance Spectroscopy,SVM,Localization,Cable Faults
终稿
Impedance spectroscopy is widely used as a cable fault location technique with high sensitivity, however, due to interference among multiple fault points, signal attenuation and complex operating environment, the obtained location curves often have some location points misjudged. In order to diagnose faults more accurately, the location results obtained should be further analyzed and judged in order to identify the true fault point and thus increase the reliability of cable operation.
In this paper, a method was proposed for the intelligent identification of cable fault points based on SVM. By establishing an impedance spectroscopy analysis model and obtaining the localization curve, the corresponding values of each point were substituted into the SVM classifier for training and testing, so as to classify the existence of faults at each point.
In this paper, the localization of cable defects is achieved by impedance spectroscopy, and the location of fault points is further obtained by training and testing the localization curve with SVM. The results show that the points on the localization curve can be classified by SVM to achieve intelligent identification of fault points.
This paper achieved intelligent identification of cable fault points based on SVM, and reduced the impact of misjudged peaks in the impedance spectrum, obtained better localization results, effectively improved the accuracy of cable fault location, and provided a new method for intelligent diagnosis of cable faults.
In this paper, a method was proposed for the intelligent identification of cable fault points based on SVM. By establishing an impedance spectroscopy analysis model and obtaining the localization curve, the corresponding values of each point were substituted into the SVM classifier for training and testing, so as to classify the existence of faults at each point.
In this paper, the localization of cable defects is achieved by impedance spectroscopy, and the location of fault points is further obtained by training and testing the localization curve with SVM. The results show that the points on the localization curve can be classified by SVM to achieve intelligent identification of fault points.
This paper achieved intelligent identification of cable fault points based on SVM, and reduced the impact of misjudged peaks in the impedance spectrum, obtained better localization results, effectively improved the accuracy of cable fault location, and provided a new method for intelligent diagnosis of cable faults.
重要日期
-
会议日期
09月25日
2022
至09月29日
2022
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08月15日 2022
提前注册日期
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09月10日 2022
报告提交截止日期
-
11月10日 2022
注册截止日期
-
11月30日 2022
初稿截稿日期
-
11月30日 2022
终稿截稿日期
主办单位
IEEE DEIS
承办单位
Chongqing University
联系方式
- Zhengyong Huang
- 61******@qq.com
历届会议
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2020年09月06日 中国 Beijing
2020 IEEE International Conference on High Voltage Engineering and Application -
2018年09月10日 希腊
2018 IEEE International Conference on High Voltage Engineering and Application -
2016年09月19日 中国 Chengdu, China
2016 IEEE International Conference on High Voltage Engineering and Application
