Vari-scale stochastic resonance system based bearing fault frequency extraction under strong noise
In order to extract the bearing faults characteristic frequency under strong noise background,a vari-scale stochastic res-onance system based useful signal enhancement method was designed.The structure and fault characteristics of bearing were in-troduced.The shortcoming of stochastic resonance theory to low noise and low frequency was analyzed,and a vari-scale stochastic resonance system was designed specifically,expanding the application scope of the theory.Then a multi-behavior particle swarm optimization algorithm for stochastic resonance system parameters optimization was proposed.Verified by simulation,under the strong noise background with a signal-to-noise ratio of-20 dB,the variable scale stochastic resonance system can still effectively extract feature frequencies from useful signals.According to the experimental data of bearings published by Xi'an Jiaotong Univer-sity,under strong noise background,the fault frequency extracted by sparse reconstruction method is still submerged in the nearby frequency domain,while the feature frequency extracted by the variable scale stochastic resonance system is significantly promi-nent,and the feature frequency extracted by the method is closer to the true value.The experimental results indicate that the vari-scale stochastic resonance theory can effectively extract the characteristic frequencies in vibration signals under strong noise back-grounds.
国家科技期刊平台
NSTL
万方数据
