A comparative study of adaptive filters in detecting a naturally degraded bearing within a gearbox

F. Elasha, D. Mba, C. Ruiz-Carcel

Research output: Contribution to journalArticle

15 Citations (Scopus)
42 Downloads (Pure)

Abstract

The diagnosis of bearing faults at the earliest stage is critical in avoiding future catastrophic failures. Many diagnostic techniques have been developed and applied in for such purposes, however, these traditional diagnostic techniques are not always successful when the bearing fault occurs within a gearbox where the vibration response is complex; under such circumstances it may be necessary to separate the bearing vibration signature. This paper presents a comparative study of four different techniques for bearing signature separation within a gearbox. The effectiveness of these individual techniques were compared in diagnosing a bearing defect within a gearbox employed for endurance tests of an aircraft control system. The techniques investigated include the least mean square (LMS), self-adaptive noise cancellation (SANC) and the fast block LMS (FBLMS). All three techniques were applied to measured vibration signals taken throughout the endurance test. In conclusion it is shown that the LMS technique detected the bearing fault earliest.
Original languageEnglish
Pages (from-to)1-8
JournalMechanical Systems and Signal Processing
Volume3
DOIs
Publication statusPublished - Nov 2017

Bibliographical note

Creative Commons License

Keywords

  • Vibration analysis
  • Condition monitoring
  • Fault
  • Bearing
  • Adaptive filters
  • Signal processing
  • Gearbox
  • Diagnostics

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