自适应移频变尺度随机共振在故障诊断中的应用  

Adaptive Frequency-Shifted and Re-Scaling Stochastic Resonance with Applications to Fault Diagnosis

作　　者：谭继勇[1] 陈雪峰[1] 雷亚国[2] 何正嘉[1] 

机构地区：[1]西安交通大学机械制造系统工程国家重点实验室,西安710049 [2]加拿大阿尔伯塔大学机械工程系,加拿大埃德蒙顿T6G2G8

出　　处：《西安交通大学学报》2009年第7期69-73,共5页Journal of Xi'an Jiaotong University

基　　金：国家重点基础研究发展计划资助项目(2005CB72410);国家高技术研究发展规划资助项目(2008AA04Z121)

摘　　要：针对移频变尺度随机共振系统参数选择困难的问题,提出了一种基于时频指标的自适应移频变尺度随机共振算法.该算法选用了最高谱峰位置(频域)及过零间距方差(时域)作为优化目标函数,避开了以信噪比等为目标函数时需要预先知道目标信号确切频率的不足,能够自适应地获取最优系统参数,以最大信噪比检测出微弱周期信号.同时,由于移频变尺度随机共振的选用,该自适应算法突破了传统随机共振系统的限制,因此可以检测实际工程中的高频信号.仿真和故障诊断的工程应用结果表明,该自适应算法简单、易于理解,能有效地从强背景噪声中检测出高频微弱周期信号,具有较强的工程实用价值.The difficulty for selecting the best system parameters restricts engineering applications to frequency-shifted and re-scaling stochastic resonance（FRSR）. An adaptive FRSR method with time-domain and frequency-domain indexes is developed, where the station of the highest spectral peak and the variance of the zero-crossing distance are chosen as the objective functions, and the optimal parameters are obtained adaptively without predicting the exact frequency of the target signal. Once FRSR is involved, the proposed method is able to detect high frequency, while the traditional stochastic resonance is only for low frequency. The simulation and engineering application on fault diagnosis indicate the ability for weak periodic signals buried in heavy noise.

关 键 词：时频指标 自适应 移频变尺度随机共振 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]