Bearing fault parameter identification under varying operating conditions using vibration signals and evolutionary algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents an effective bearing fault parameter identification scheme based on evolutionary optimization techniques. Three seeded faults in the rotating machinery supported by the test roller bearing include inner race fault, outer race fault and a single ball defect. The fault related features are extracted experimentally by processing the acquired vibration signals in both the time and frequency domain. Techniques based on the power spectral density (PSD) and wavelet transform (WT) are utilized for feature extraction. The sensitivity of the proposed method is investigated under varying operating speeds and radial bearing load. In this study, the inverse problem of parameter identification is investigated. The problem of parameter identification is recast as an optimization problem and two well known evolutionary algorithms, differential evolution (DE) and particle swarm optimization (PSO), are used to identify system parameters given a system response. For online parameter identification, differential evolution outperforms particle both in terms of adaptability and tighter convergence properties. The distinction between the two methods is not distinctively obvious on the offline parameter identification problem.

Original languageEnglish (US)
Title of host publicationDynamics, Vibration, and Control
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791846483
DOIs
StatePublished - Jan 1 2014
EventASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014 - Montreal, Canada
Duration: Nov 14 2014Nov 20 2014

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume4B

Other

OtherASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014
CountryCanada
CityMontreal
Period11/14/1411/20/14

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

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