Enhanced fault diagnosis via stochastic resonance in a piecewise asymmetric bistable system release_xabf3heiqvanflajzicjwhatbq

by Yongge Li, Qixiao Zhu, Yong Xu, Ruilan Tian

Published in Chaos by AIP Publishing.

2024   Volume 34, Issue 1

Abstract

Weak fault signals are often overwhelmed by strong noise or interference. The key issue in fault diagnosis is to accurately extract useful fault characteristics. Stochastic resonance is an important signal processing method that utilizes noise to enhance weak signals. In this paper, to address the issues of output saturation and imperfect optimization of potential structure models in classical bistable stochastic resonance (CBSR), we propose a piecewise asymmetric stochastic resonance system. A two-state model is used to theoretically derive the output signal-to-noise ratio (SNR) of the bistable system under harmonic excitations, which is compared with the SNR of CBSR to demonstrate the superiority of the method. The method is then applied to fault data. The results indicate that it can achieve a higher output SNR and higher spectral peaks at fault characteristic frequencies/orders, regardless of whether the system operates under fixed or time-varying speed conditions. This study provides new ideas and theoretical guidance for improving the accuracy and reliability of fault diagnosis technology.
In application/xml+jats format

Archived Files and Locations

application/pdf   2.4 MB
file_fzh3gedblbfyth7exv3upfq4fm
watermark.silverchair.com (publisher)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2024-01-01
Language   en ?
DOI  10.1063/5.0188335
PubMed  38285724
Container Metadata
Not in DOAJ
In Keepers Registry
ISSN-L:  1054-1500
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 62657198-d307-4470-bef3-d1629c5170fb
API URL: JSON