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

24 Citations (SciVal)
265 Downloads (Pure)


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
Early online date19 Dec 2016
Publication statusPublished - Jul 2017


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


Dive into the research topics of 'Phase editing as a signal pre-processing step for automated bearing fault detection'. Together they form a unique fingerprint.

Cite this