Reliability assessment of rolling bearing based on principal component analysis and Weibull proportional hazard model

Reliability assessment is s a critical consideration in regards to equipments proactive maintenance. Selecting the features which can accurately reflect the performance degradation process as the inputs of the reliability assessment model is the precondition of accurate reliability assessment. A novel method based on principal component analysis (PCA) and weibull proportional hazards model (WPHM) is proposed to assess the reliability of the rolling bearing. A high relative feature set is constructed by selecting the effective features through extracting the time domain, frequency domain and time-frequency domain features of lifetime bearing. The principal components (PCs) which can accurately reflect the performance degradation process are obtained by PCA. Then the PCs are used as the covariates of WPHM to assess the reliability. An example of bearing test is used to verify the ability of the proposed method. Meanwhile, as the relative features are extracted, the differences in manufacturing, installation and working condition of the same type bearings are reduced, which enhances the practicability and stability of the method.

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