Corrosion fault identification model of substation grounding grid based on PSO-LS-SVM
Qin J(秦军)2; Miao J(缪金)2; Wu X(吴曦)2; Wang ZB(王资博)2; Shao S(邵帅)1,3,4
2021
会议日期May 22-24, 2021
会议地点Kunming, China
页码1-8
英文摘要As one of the important equipment to ensure the normal operation of substation, the performance of grounding grid has been highly concerned. In recent years, researchers propose that the theory of electromagnetic induction can be used to diagnose and identify the corrosion fault of substation grounding grid. In this paper, a fault classification model based on LS-SVM optimized by PSO is proposed to identify the corrosion fault of grounding grid. Firstly, the wavelet packet transform principle is used to filter the original data, and the wavelet packet energy is used to construct the fault eigenvalue as the input of the fault classification model. Based on LS-SVM, a corrosion fault classification model is constructed, and particle swarm optimization method is used to optimize the parameters of the model, which solves the problem of traditional SVM parameter optimization. Through the practical application in substation, the model proposed in this paper can identify the corrosion of grounding grid conductor without excavation and power failure, which provides an effective scheme for engineering application.
产权排序2
会议录4th International Conference on Mechanical, Electric and Industrial Engineering, MEIE 2021
会议录出版者IOP
会议录出版地Bristol, UK
语种英语
ISSN号1742-6588
WOS记录号IOP:1742-6588-1983-1-012092
内容类型会议论文
源URL[http://ir.sia.cn/handle/173321/29506]  
专题沈阳自动化研究所_工业控制网络与系统研究室
通讯作者Shao S(邵帅)
作者单位1.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China
2.State Grid Wuxi Power Supply Company, Wuxi, Jiangsu, China
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
4.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China
推荐引用方式
GB/T 7714
Qin J,Miao J,Wu X,et al. Corrosion fault identification model of substation grounding grid based on PSO-LS-SVM[C]. 见:. Kunming, China. May 22-24, 2021.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace