A Monotonic Degradation Assessment Index of Rolling Bearings Using Fuzzy Support Vector Data Description and Running Time

Sensors

Zhongjie Shen²  Zhengjia He¹  Xuefeng Chen²  Chuang Sun² 

[1] State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China;

关键词: performance degradation assessment;    fuzzy support vector data description;    running time;    run-to-failure test;    operation reliability;   

DOI  :  10.3390/s120810109

来源: mdpi

【 摘 要 】

Performance degradation assessment based on condition monitoring plays an important role in ensuring reliable operation of equipment, reducing production downtime and saving maintenance costs, yet performance degradation has strong fuzziness, and the dynamic information is random and fuzzy, making it a challenge how to assess the fuzzy bearing performance degradation. This study proposes a monotonic degradation assessment index of rolling bearings using fuzzy support vector data description (FSVDD) and running time. FSVDD constructs the fuzzy-monitoring coefficient ε̄ which is sensitive to the initial defect and stably increases as faults develop. Moreover, the parameter ε̄ describes the accelerating relationships between the damage development and running time. However, the index ε̄ with an oscillating trend disagrees with the irreversible damage development. The running time is introduced to form a monotonic index, namely damage severity index (DSI). DSI inherits all advantages of ε̄ and overcomes its disadvantage. A run-to-failure test is carried out to validate the performance of the proposed method. The results show that DSI reflects the growth of the damages with running time perfectly.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.