Dynamic wavelet-based tool for gearbox diagnosis

Farag K. Omar, A. M. Gaouda

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


This paper proposes a novel wavelet-based technique for detecting and localizing gear tooth defects in a noisy environment. The proposed technique utilizes a dynamic windowing process while analyzing gearbox vibration signals in the wavelet domain. The gear vibration signal is processed through a dynamic Kaisers window of varying parameters. The window size, shape, and sliding rate are modified towards increasing the similarity between the non-stationary vibration signal and the selected mother wavelet. The window parameters are continuously modified until they provide maximum wavelet coefficients localized at the defected tooth. The technique is applied on laboratory data corrupted with high noise level. The technique has shown accurate results in detecting and localizing gear tooth fracture with different damage severity.

Original languageEnglish
Pages (from-to)190-204
Number of pages15
JournalMechanical Systems and Signal Processing
Issue number1
Publication statusPublished - Jan 2012


  • Gear tooth failure
  • Machine diagnostics
  • Wavelet multi-resolution

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Civil and Structural Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications


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