低压断路器振动信号小波包分析及开关同步研究

Xi-ren Miao, Yan Wang
{"title":"低压断路器振动信号小波包分析及开关同步研究","authors":"Xi-ren Miao, Yan Wang","doi":"10.1109/ICSSEM.2012.6340820","DOIUrl":null,"url":null,"abstract":"Wavelet decomposition method is used to analysis the vibration signal of low voltage circuit breaker mechanical properties. According to the electric operating mechanism and circuit breaker closing action sequence relations, drive motor current signal as a time stamp is applied to effectively extract switching vibration signal. Then, vibration signal feature vectors are structured by means of the wavelet packet energy spectrum, and BP neural network are applied to establish the three-phase closing asynchronous fault identification model. The experiment and simulation results show that the combination of wavelet packet energy spectrum and neural network can effectively analysis of low voltage circuit breaker closing synchronism.","PeriodicalId":115037,"journal":{"name":"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization","volume":"147 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Vibration signal wavelet packet analysis and switching synchronization research of low voltage circuit breaker\",\"authors\":\"Xi-ren Miao, Yan Wang\",\"doi\":\"10.1109/ICSSEM.2012.6340820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wavelet decomposition method is used to analysis the vibration signal of low voltage circuit breaker mechanical properties. According to the electric operating mechanism and circuit breaker closing action sequence relations, drive motor current signal as a time stamp is applied to effectively extract switching vibration signal. Then, vibration signal feature vectors are structured by means of the wavelet packet energy spectrum, and BP neural network are applied to establish the three-phase closing asynchronous fault identification model. The experiment and simulation results show that the combination of wavelet packet energy spectrum and neural network can effectively analysis of low voltage circuit breaker closing synchronism.\",\"PeriodicalId\":115037,\"journal\":{\"name\":\"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization\",\"volume\":\"147 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSEM.2012.6340820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2012.6340820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

采用小波分解方法对低压断路器的振动信号进行力学性能分析。根据电动操动机构和断路器合闸动作顺序关系,采用驱动电机电流信号作为时间戳,有效提取开关振动信号。然后,利用小波包能谱构造振动信号特征向量,并应用BP神经网络建立三相合拢异步故障识别模型;实验和仿真结果表明,将小波包能谱与神经网络相结合可以有效地分析低压断路器合闸同步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vibration signal wavelet packet analysis and switching synchronization research of low voltage circuit breaker
Wavelet decomposition method is used to analysis the vibration signal of low voltage circuit breaker mechanical properties. According to the electric operating mechanism and circuit breaker closing action sequence relations, drive motor current signal as a time stamp is applied to effectively extract switching vibration signal. Then, vibration signal feature vectors are structured by means of the wavelet packet energy spectrum, and BP neural network are applied to establish the three-phase closing asynchronous fault identification model. The experiment and simulation results show that the combination of wavelet packet energy spectrum and neural network can effectively analysis of low voltage circuit breaker closing synchronism.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信