Application of the Wavelet Multi-resolution Analysis and Hilbert transform for the prediction of gear tooth defects

A. Djebala, N. Ouelaa, C. Benchaabane, D. F. Laefer

Research output: Contribution to journalArticlepeer-review

Abstract

In machine defect detection, namely those of gears, the major problem is isolating the defect signature from the measured signal, especially where there is significant background noise or multiple machine components. This article presents a method of gear defect detection based on the combination of Wavelet Multi-resolution Analysis and the Hilbert transform. The pairing of these techniques allows simultaneous filtering and denoising, along with the possibility of detecting transitory phenomena, as well as a demodulation. This paper presents a numerical simulation of the requisite mathematical model followed by its experimental application of acceleration signals measured on defective gears on a laboratory test rig. Signals were collected under various gear operating conditions, including defect size, rotational speed, and frequency bandwidth. The proposed method compares favourably to commonly used analysis tools, with the advantage of enabling defect frequency isolation, thereby allowing detection of even small or combined defects.

Original languageEnglish (US)
Pages (from-to)1601-1612
Number of pages12
JournalMeccanica
Volume47
Issue number7
DOIs
StatePublished - Oct 2012

Keywords

  • Demodulation
  • Gears defects
  • Hilbert transform
  • Vibratory analysis
  • Wavelet multi-resolution analysis

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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