Wang Baocheng, Li Danhe, Sun Xiaofeng, Wu Wei-yang
{"title":"The studies of Single-phase Inverter Fault Diagnosis Based on D-S Evidential Theory and Fuzzy Logical Theory","authors":"Wang Baocheng, Li Danhe, Sun Xiaofeng, Wu Wei-yang","doi":"10.1109/IPEMC.2006.4778350","DOIUrl":null,"url":null,"abstract":"A data fusion method for single-phase inverter fault diagnosis based on D-S evidential theory and fuzzy logical theory is presented. By measuring the output voltage the two bridge-arms voltage and the temperature of MOSFET, the belief function assignment is obtained, and the fusion belief function assignment is obtained by using D-S rule and fuzzy logic, and fault component is found. By comparing the diagnosis results based on separate original data and fused data respectively, it is shown that the latter is more accurate than the former in the fault recognition","PeriodicalId":448315,"journal":{"name":"2006 CES/IEEE 5th International Power Electronics and Motion Control Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 CES/IEEE 5th International Power Electronics and Motion Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPEMC.2006.4778350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
A data fusion method for single-phase inverter fault diagnosis based on D-S evidential theory and fuzzy logical theory is presented. By measuring the output voltage the two bridge-arms voltage and the temperature of MOSFET, the belief function assignment is obtained, and the fusion belief function assignment is obtained by using D-S rule and fuzzy logic, and fault component is found. By comparing the diagnosis results based on separate original data and fused data respectively, it is shown that the latter is more accurate than the former in the fault recognition