首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Adaptive Stochastic Resonance-Based Processing of Weak Magnetic Slippage Signals of Bearings
Authors:Jianpeng Ma  Chengwei Li  Guangzhu Zhang
Institution:1.School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;2.Songsim Global Campus, Undergraduate College, The Catholic University of Korea, Bucheon-si 14662, Korea;
Abstract:Slip is one of the most common forms of failure in aviation bearings, and it can pose a great threat to the stable operation of aviation bearings. Bearing cage speed monitoring methods based on weak magnetic detection can achieve nondestructive measurements. However, the method suffers from solid signal background noise due to the high sensitivity of the sensor. Therefore, in this paper, an adaptive stochastic resonance algorithm was proposed in response to the characteristics of the weak magnetic detection signal and the problem of solid noise. In addition, by adaptively adjusting the coefficients of the stochastic resonance system—by an improved moth flame optimization algorithm—the drawback in which the stochastic resonance method required artificially set parameters for extracting the feature frequencies of the weak magnetic signals was solved. In this process, we used parameters, such as general refined composite multi-scale sample entropy, as the adaptation function of the optimization algorithm. In the end, simulation and experimental outcomes verified the efficacy of the approach put forward.
Keywords:bearing weak magnetic signal  stochastic resonance  adaptive algorithm  feature extraction  slip rate
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号