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Research On Reliability Assessment And Remaining Useful Life Prediction Of Rolling Bearing

Posted on:2018-07-01Degree:MasterType:Thesis
Country:ChinaCandidate:X T ChenFull Text:PDF
GTID:2322330536461479Subject:Mechanical Manufacturing and Automation
Abstract/Summary:PDF Full Text Request
The rolling bearing is one of the most basic and easily damageable parts of rotating machinery,and its running state directly decides the health of the key equipment.Hence,it is of great significance to study the reliability assessment and remaining useful life prediction of rolling bearing.In this paper,taking the life cycle vibration signals of rolling bearing as the research object,the reliability assessment and remaining useful life prediction of rolling bearing were conducted based on Weibull proportional hazards model,and the two key problems of the model were taken deep study to put forward effective solutions.The main contents of the paper are as follows:(1)Discuss the background and significance of the study,describe the research status of rolling bearing life prediction at home and abroad,and analyze the two key problems in the life prediction of rolling bearing.Introduce the structure and failure form of rolling bearing,analysis the fault characteristics of rolling bearing,lead in feature extraction method based on vibration signal,and introduce the time domain,frequency domain and time-frequency feature extraction method to establish the theoretical foundation for the following study.(2)Selecting the features which can accurately reflect the performance degradation process as the covariates of WPHM is the premise of improving the accuracy of reliability assessment and remaining useful life prediction.For the shortcoming of WPHM covariate selection,a new method of kernel principal component analysis feature extraction for rolling bearing based on multi-domain was proposed.The time domain,frequency domain and timefrequency features which can comprehensively reflect the performance degradation of rolling bearings were extracted,and then the kernel principal component analysis was carried out.Then the features which can reflect the performance degradation of rolling bearings were taken as the covariates of WPHM to perform reliability assessment.The validity of the method was verified by the life cycle data of rolling bearings.(3)Accurate trend prediction is the key to ensuring the accuracy of remaining useful life prediction.For the shortcoming of WPHM trend prediction method,the shortcomings of gray model are analyzed based on the characteristics of covariates and failure rate data,and a new method of the trend prediction based on pchip interpolation-EEMD-GM(1,1)model was proposed.Select different time points to predict the failure rate trend,calculate the reliability life,predict the remaining useful life of rolling bearings.The effectiveness of the method was verified by the life cycle data of rolling bearings,and the pros and cons of covariate trend prediction and failure rate trend prediction was verified.(4)On the basis of the previous theoretical analysis and algorithm,a system of the rolling bearing reliability assessment and remaining useful life prediction was developed by taking full advantage of LabVIEW and MATLAB.The system was divided into four modules: user setting,life cycle monitoring,reliability assessment,and remaining useful life prediction.
Keywords/Search Tags:Rolling bearing, Proportional hazards model, Performance degradation assessment, Reliability assessment, Remaining useful life prediction
PDF Full Text Request
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