Bearing fault diagnosis based on a new acoustic emission sensor technique

Brandon Van Hecke, Yongzhi Qu, David He

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


The diagnosis of bearing health by quantifying acoustic emission data has been an area of interest for recent years due to the numerous advantages over vibration-based techniques. However, most acoustic emission-based methodologies to date are data-driven technologies. This research takes a novel approach combining a heterodyne-based frequency reduction technique, time synchronous resampling, and spectral averaging to process acoustic emission signals and extract condition indicators for bearing fault diagnosis. The heterodyne technique allows the acoustic emission signal frequency to be shifted from several megahertz to less than 50 kHz, which is comparable to that of vibration-based techniques. Then, the digitized signal is band-pass filtered to retain the information associated with the bearing defects. Finally, the tachometer signal is used to time synchronously resample the acoustic emission data, allowing the computation of a spectral average which in turn enables the extraction and evaluation of condition indicators for bearing fault diagnosis. The presented technique is validated using the acoustic emission signals of seeded fault steel bearings on a bearing test rig. The result is an effective acoustic emission-based approach validated to diagnose all four fault types: inner race, outer race, ball, and cage.

Original languageEnglish (US)
Pages (from-to)105-118
Number of pages14
JournalProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Issue number2
StatePublished - Apr 2 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© IMechE 2014.


  • Acoustic emission sensor
  • bearing
  • fault diagnosis


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