Multi-scale morphology analysis of acoustic emission signal and quantitative diagnosis for bearing fault |
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Authors: | Wen-Jing Wang Ling-Li Cui Dao-Yun Chen |
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Institution: | 1. School of Mechanical, Electronic and Control Engineering,Beijing Jiaotong University, Beijing 100044, China;2. College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology,Beijing 100124, China |
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Abstract: | Monitoring of potential bearing faults in operation is of critical importance to safe operation of high speed trains. One of the major challenges is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment. In this work, we report a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum (MPS) through a multi-scale morphology analysis procedure. The results show that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves. Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes. |
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Keywords: | Bearing fault Acoustic emission Morphological pattern spectrum (MPS) Sample entropy Lempel-Ziv complexity |
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