Phase editing as a signal pre-processing step for automated bearing fault detection

Leonardo Barbini, Agusmian P. Ompusunggu, Andrei Bartic, Andrew Hillis, Jonathan Du Bois

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
176 Downloads (Pure)

Abstract

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance.However automation of the detection process is difficult due to the complexity ofvibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator.This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally efficient full band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state of the artprocessing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates comparedto the state of the art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.
Original languageEnglish
Pages (from-to)407-421
JournalMechanical Systems and Signal Processing
Volume91
Early online date19 Dec 2016
DOIs
Publication statusPublished - Jul 2017

Keywords

  • Phase spectrum
  • Automated diagnostics of defective bearings
  • Spectral kurtosis
  • Cepstrum pre-whitening;

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