{"title":"Development of an experimental software for rub-impact fault recognition research","authors":"Yanjun Lu, L. Wan, Yi Liu","doi":"10.1109/CCDC.2015.7162737","DOIUrl":null,"url":null,"abstract":"Rotor and stator rubbing is a common fault of rotating machinery, for instance, aircraft engine, currently, numerous methods are presented to address the issues of Rub-impact fault. For the purpose of effective research for the different diagnosis methods, a experimental system for Rub-Impact fault diagnosis research is achieved in this paper, with the mixed programming of Matlab and VC++ applied. As an illustration, three methods, such as Linear-SVM, RBF-SVM and BP network, are embedded and the respective diagnosis results are analyzed. In addition, a brief introduction of mixed programming with Visual C ++ and MatLAB and the system architecture are given in this paper. The application of software platform gives the results that the system presented is practical and effective in fact.","PeriodicalId":273292,"journal":{"name":"The 27th Chinese Control and Decision Conference (2015 CCDC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 27th Chinese Control and Decision Conference (2015 CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2015.7162737","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
Rotor and stator rubbing is a common fault of rotating machinery, for instance, aircraft engine, currently, numerous methods are presented to address the issues of Rub-impact fault. For the purpose of effective research for the different diagnosis methods, a experimental system for Rub-Impact fault diagnosis research is achieved in this paper, with the mixed programming of Matlab and VC++ applied. As an illustration, three methods, such as Linear-SVM, RBF-SVM and BP network, are embedded and the respective diagnosis results are analyzed. In addition, a brief introduction of mixed programming with Visual C ++ and MatLAB and the system architecture are given in this paper. The application of software platform gives the results that the system presented is practical and effective in fact.