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论文类型：会议论文

发表时间：2013-01-01

收录刊物：CPCI-S、Scopus

页面范围：1730-1733

关键字：rolling bearing; reliability estimation; logistic regression model; vibration; feature extraction

摘要：Rolling bearing (RB) has been broadly applied on mechanical systems. Its reliability is directly related to the performance of the whole mechanical system. RB reliability estimation technology is crucial for mechanical system. Logistic regression model (LRM) is constructed for RB reliability estimation in this paper. Vibration data acquisition and feature extraction are carried on for. Based on feature extraction investigation, root mean square and wavelet entropy are used to construct characteristics vector. Therefore, bearing degradation state information is determined by vibration information. Reliability estimation model based on LRM is constructed to estimate bearing performance. By using LRM, it has good performance on reliability estimation. It can be concluded that LRM is beneficial for RB life prediction.