Rolling bearing state assessment based on the composite multiscale weight slope entropy and hierarchical prototype-based approach

Advances in Mechanical Engineering

Research Article

Cheng Wang¹  Jixuan Bian¹  Jinle Zhang¹  Jinbao Zhang¹  Zhengyang Pan² 

[1] China North Vehicle Research Institute, Beijing, China;School of Software Engineering, A National Pilot Software College, Faculty of Information Technology, Beijing University of Technology, Beijing, China;

关键词: Rolling bearing;    state assessment;    vibration signals;    composite multiscale weight slope entropy;    hierarchical prototype-based approach;   

DOI  :  10.1177/16878132221137419

 received in 2022-08-17, accepted in 2022-10-20,  发布年份 2022

来源: Sage Journals

【 摘 要 】

To evaluate the state of rolling bearing more accurately, a new feature called composite multiscale weight slope entropy was proposed for the complexity measurement of vibration signals. On the basis of analyzing the fault signal structure, the new feature could consider the influence of the nonlinearity, the multiscale characteristics, the fluctuation of the amplitude, and the amplitude itself on the fault signals. In the following, different fault types and the corresponding damage degree of rolling bearings were identified with the hierarchical prototype-based approach. Compared with the results of different modified slope entropy, it is shown that composite multiscale weight slope entropy could significantly improve the identification accuracy. In the two designed testing schemes, ten and sixty state types of rolling bearings are respectively calculated, and the identification accuracy could reach up to 100% and 96.5% respectively, which illustrate the effectiveness and the validity of the proposed approach.

【 授权许可】

CC BY   
© The Author(s) 2022

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