Chenyu Xiao, Ming Yu, Xin Liu, Xiaozheng Jin, Canghua Jiang
{"title":"Distributed Fault Estimation of Complex System Using Improved Biogeography-Based Optimization","authors":"Chenyu Xiao, Ming Yu, Xin Liu, Xiaozheng Jin, Canghua Jiang","doi":"10.1109/phm-qingdao46334.2019.8943020","DOIUrl":null,"url":null,"abstract":"This paper deals with distributed fault estimation of complex system using bond graph and improved biogeography- based optimization. Firstly, a system decomposition method is used where the complex system is decomposed into several minimal subsystems. Then, distributed analytical redundancy relations and distributed fault signature matrix derived from subsystems diagnostic bond graphs are used for distributed fault detection and isolation respectively. When a set of possible faults are obtained through distributed fault isolation, an improved biogeography-based optimization is proposed for distributed fault estimation. Finally, taking a complex circuit system as an example, numerical simulations are performed to illustrate the effectiveness of the developed method.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/phm-qingdao46334.2019.8943020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper deals with distributed fault estimation of complex system using bond graph and improved biogeography- based optimization. Firstly, a system decomposition method is used where the complex system is decomposed into several minimal subsystems. Then, distributed analytical redundancy relations and distributed fault signature matrix derived from subsystems diagnostic bond graphs are used for distributed fault detection and isolation respectively. When a set of possible faults are obtained through distributed fault isolation, an improved biogeography-based optimization is proposed for distributed fault estimation. Finally, taking a complex circuit system as an example, numerical simulations are performed to illustrate the effectiveness of the developed method.