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| Roller bearing operation reliability prediction based on Relevance Vector Machine and normalized wavelet decomposition information entropy |
| CHEN Fafa1，LIU Lili1，LIU Furong1，XIAO Wenrong1，CHEN Baojia1，YANG Yong2 |
| 1.Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance, China Three Gorges University, Yichang 443002, China;
2.China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China |
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Abstract Aimed at traditional methods are difficult to achieve reliability evaluation and prediction for a single serving machine, an operation reliability evaluation and prediction method based on normalized wavelet information entropy and Relevance Vector Machine was proposed in this paper.This method mainly includes the establishment of an operational reliability index and the construction of a Relevance Vector Machine prediction model.Firstly, the vibration signals of roller bearings in the operation process were acquired in a test experiment.The features which reflected roller bearings running status were extracted from the vibration signals using wavelet packet decomposition.Then, the operation reliability index was established based on information entropy theory.Finally, a Relevance Vector Machine prediction model was constructed to predict the operation reliability index and its changing trend for the actual roller bearing.The experiment results show that the operation reliability evaluation and prediction method by using the normalized wavelet information entropy and Relevance Vector Machine, can effectively overcome the traditional calculation problem with probability statistics, and obtain the better operation reliability result for a single serving machine.
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Received: 13 September 2018
Published: 15 April 2020
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| Cite this article: |
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CHEN Fafa1,LIU Lili1,LIU Furong1, et al. Roller bearing operation reliability prediction based on Relevance Vector Machine and normalized wavelet decomposition information entropy[J]. JOURNAL OF VIBRATION AND SHOCK, 2020, 39(8): 8-14.
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| URL: |
| http://jvs.sjtu.edu.cn/EN/ OR http://jvs.sjtu.edu.cn/EN/Y2020/V39/I8/8 |
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