{"title":"基于数据缺失和特征转移抑制策略的轴承故障诊断","authors":"Yunji Zhao, Jun Xu","doi":"10.1177/09596518241237080","DOIUrl":null,"url":null,"abstract":"To mitigate the impact of fault iconic feature shift and feature missing due to missing data values on bearing fault diagnosis, this paper proposes a fault diagnosis method based on a spatial frequency filter and a Multi-Scale feature recombination calibration network (MSRCN). First, the fault features are converted into frequency band features and feature enhancement is realized using Mel filters to weaken the effect of fault feature offset. Then, the spatial calibration module (SC) in the MSRCN is utilized to further improve the fault feature distribution and eliminate the fault feature offset problem. Next, to solve the fault feature missing problem, the remaining fault features are sampled by multi-scale reorganization using MSRCN to obtain new fault features, which overcomes the effect of fault feature missing on fault diagnosis. Finally, experiments are conducted on CWRU and XJTU-SY rolling bearing datasets to verify that the algorithm can effectively solve the fault feature offset and missing problem. Meanwhile, the experimental results prove that the algorithm proposed in this paper can realize high-precision fault diagnosis.","PeriodicalId":20638,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering","volume":"101 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bearing fault diagnosis based on data missing and feature shift suppression strategy\",\"authors\":\"Yunji Zhao, Jun Xu\",\"doi\":\"10.1177/09596518241237080\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To mitigate the impact of fault iconic feature shift and feature missing due to missing data values on bearing fault diagnosis, this paper proposes a fault diagnosis method based on a spatial frequency filter and a Multi-Scale feature recombination calibration network (MSRCN). First, the fault features are converted into frequency band features and feature enhancement is realized using Mel filters to weaken the effect of fault feature offset. Then, the spatial calibration module (SC) in the MSRCN is utilized to further improve the fault feature distribution and eliminate the fault feature offset problem. Next, to solve the fault feature missing problem, the remaining fault features are sampled by multi-scale reorganization using MSRCN to obtain new fault features, which overcomes the effect of fault feature missing on fault diagnosis. Finally, experiments are conducted on CWRU and XJTU-SY rolling bearing datasets to verify that the algorithm can effectively solve the fault feature offset and missing problem. Meanwhile, the experimental results prove that the algorithm proposed in this paper can realize high-precision fault diagnosis.\",\"PeriodicalId\":20638,\"journal\":{\"name\":\"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering\",\"volume\":\"101 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1177/09596518241237080\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/09596518241237080","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Bearing fault diagnosis based on data missing and feature shift suppression strategy
To mitigate the impact of fault iconic feature shift and feature missing due to missing data values on bearing fault diagnosis, this paper proposes a fault diagnosis method based on a spatial frequency filter and a Multi-Scale feature recombination calibration network (MSRCN). First, the fault features are converted into frequency band features and feature enhancement is realized using Mel filters to weaken the effect of fault feature offset. Then, the spatial calibration module (SC) in the MSRCN is utilized to further improve the fault feature distribution and eliminate the fault feature offset problem. Next, to solve the fault feature missing problem, the remaining fault features are sampled by multi-scale reorganization using MSRCN to obtain new fault features, which overcomes the effect of fault feature missing on fault diagnosis. Finally, experiments are conducted on CWRU and XJTU-SY rolling bearing datasets to verify that the algorithm can effectively solve the fault feature offset and missing problem. Meanwhile, the experimental results prove that the algorithm proposed in this paper can realize high-precision fault diagnosis.
期刊介绍:
Systems and control studies provide a unifying framework for a wide range of engineering disciplines and industrial applications. The Journal of Systems and Control Engineering refleSystems and control studies provide a unifying framework for a wide range of engineering disciplines and industrial applications. The Journal of Systems and Control Engineering reflects this diversity by giving prominence to experimental application and industrial studies.
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This journal is a member of the Committee on Publication Ethics (COPE).cts this diversity by giving prominence to experimental application and industrial studies.