{"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}
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.