{"title":"Fault diagnosis of rolling bearing based on time and frequency domain analysis and EMD","authors":"Liandie Zhu, W. Dai, Guixiu Luo, Rui Du","doi":"10.1109/phm-qingdao46334.2019.8942926","DOIUrl":null,"url":null,"abstract":"Prognostic and health management (PHM) technology is the use of a large amount of condition monitoring data and information, with the help of all kinds of fault model and artificial intelligence algorithms monitoring, diagnosis, prediction and management of the health status of the equipment technology, by predicting the problems and reliable working life, improving the safety of equipment, minimizing the fault effect, this article in rolling bearing, using Labview software construction time domain analysis program, the analysis of three kinds of condition from different perspective (35Hz12KN/37.5Hz11KN/40HZ10KN)under the rolling bearing, Finally, Matlab software was used for frequency domain analysis and empirical mode decomposition (EMD), and the inherent modal function and vibration signal spectrum were extracted to find out the fault characteristic frequency band, which provided a basis for bearing fault diagnosis under different loads.","PeriodicalId":259179,"journal":{"name":"2019 Prognostics and System Health Management Conference (PHM-Qingdao)","volume":"117 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-qingdao46334.2019.8942926","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
Prognostic and health management (PHM) technology is the use of a large amount of condition monitoring data and information, with the help of all kinds of fault model and artificial intelligence algorithms monitoring, diagnosis, prediction and management of the health status of the equipment technology, by predicting the problems and reliable working life, improving the safety of equipment, minimizing the fault effect, this article in rolling bearing, using Labview software construction time domain analysis program, the analysis of three kinds of condition from different perspective (35Hz12KN/37.5Hz11KN/40HZ10KN)under the rolling bearing, Finally, Matlab software was used for frequency domain analysis and empirical mode decomposition (EMD), and the inherent modal function and vibration signal spectrum were extracted to find out the fault characteristic frequency band, which provided a basis for bearing fault diagnosis under different loads.