改进势函数随机共振在轴承故障检测中的应用  

Application of improved potential function stochastic resonance system in bearing fault detection

作　　者：张刚[1] 周林[1] 张天骐[1] Zhang Gang;Zhou Lin;Zhang Tianqi(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《电子测量与仪器学报》2018年第12期134-141,共8页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金项目(61771085;61371164);信号与信息处理重庆市市级重点实验室建设项目(CSTC2009CA2003);重庆市教育委员会科研项目(KJ1600427;KJ1600429)资助

摘　　要：针对经典双稳随机共振(CBSR)系统的输出饱和性与参数难以独立调节的问题,在势函数随机共振(PSR)系统基础上,叠加一个线性项,提出了改进PSR(IPSR)系统。可更加灵活的改变势函数形状,获得更好的检测效果。以输出信噪比为衡量指标,探究了系统参数a、f以及噪声强度D对系统输出的作用规律;针对大频率输入信号,先进行预处理,再通过自适应算法对参数寻优。仿真结果表明,IPSR系统检测效果优于PSR与CBSR系统。将IPSR系统应用于轴承故障检测并与PSR系统的检测效果进行对比,实验结果显示,在外圈故障检测中,输出信噪比高出2.113 5 dB;在内圈故障检测中,输出信噪比高出1.474 5 dB,有着更好的检测效果。In order to solve the problem that the output saturation and parameters of the CBSR system are difficult to adjust independently,based on the PSR system,a linear term is superimposed and an IPSR system is proposed. It is more flexible to change the shape of the potential function for better detection results. Taking the output signal-to-noise ratio as the measurement index,the effects of system parameters a,fand noise intensity D on the system output are explored. For the large-frequency input signal,the preprocessing is performed first,then the parameters are optimized by the adaptive algorithm. The simulation results show that the detection effect of IPSR system is better than that of PSR and CBSR system. Finally,the IPSR system is applied to bearing fault detection and compare with the PSR system. The experimental results show that in the outer ring fault detection,the output signal-to-noise ratio is 2. 113 5 dB higher;in the inner ring fault detection,the output signal-to-noise ratio is 1. 474 5 dB higher,which have a better detection results.

关 键 词：PSR系统 IPSR系统 随机共振 输出信噪比 轴承故障检测 

分 类 号：TH133.3[机械工程—机械制造及自动化]