Weak Fault Signal Detection of Rotating Machinery Based on Multistable Stochastic Resonance and VMD-AMD

Dongying Han,Peiming Shi,Xiao Su

doi:10.1155/2018/4252438

Abstract

For solving detection problems of multifrequency weak signals in noisy background, a novel weak signal detection method based on variational mode decomposition (VMD) and rescaling frequency-shifted multistable stochastic resonance (RFMSR) with analytical mode decomposition (AMD) is proposed. In this method, different signal frequency bands are processed by rescaling subsampling compression to make each frequency band meet the conditions of stochastic resonance. Before the enhanced signal components are synthesized, they are processed to achieve the enhanced signal by means of AMD, leaving only the enhanced sections of the signal. The processed signal is decomposed into intrinsic mode functions (IMF) by VMD, in order to require the detection of weak multifrequency signals. The experimental analysis of the rolling bearing inner ring fault and gear fault diagnosis demonstrate that the proposed method can not only enhance signal amplitude, reduce false components, and improve the VMD algorithm’s accuracy, but also effectively detect weak multifrequency signals submerged by noise.

Highlights

Because rotating machinery has come to play an increasingly significant role in transportation and industrial production, mechanical faults and damage, bearing and gear faults, have recently been the cause of greater catastrophes and losses
In order to overcome these constraints, we propose a method based on the variational mode decomposition (VMD) following denoising by rescaling frequency-shifted multistable stochastic resonance (RFMSR) with analytical mode decomposition (AMD), for better extracting the characteristic frequency and to observe clearly the VMD decomposition results
In order to address the detection problems in multifrequency signals in noisy backgrounds, a novel method based on VMD after denoising by RFMSR with AMD is proposed

Summary

Introduction

Because rotating machinery has come to play an increasingly significant role in transportation and industrial production, mechanical faults and damage, bearing and gear faults, have recently been the cause of greater catastrophes and losses. The first involves obtaining a useful signal by eliminating or suppressing noise Standard techniques, such as the wavelet denoising method, analytical mode decomposition (AMD), empirical mode decomposition (EMD) method, ensemble empirical mode decomposition (EEMD), local mean decomposition (LMD) method, and variational mode decomposition (VMD), inevitably weaken the useful signal while removing noise. Leng et al [36] developed methods for transforming a high frequency into a low frequency, based on frequency rescaling or modulation, in order to satisfy the traditional SR requirements These studies provide methods for the application of SR technology in processing large parameters signals. A novel method is proposed based on VMD after denoising, by means of rescaling frequencyshifted multistable SR with AMD.

Multistable SR with Analytical Mode Decomposition

Application of Proposed Method

Conclusion