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Spur bevel gearbox fault diagnosis using wavelet packet transform for feature extraction

  • Wentao Huang*
  • , Peilu Niu
  • , Xiaojun Lu
  • *Corresponding author for this work
  • School of Mechatronics Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Gear as an important transmission component in the production of modern industrial, used in all areas of production and life, its stable and reliable work has great social significance. In this paper, gear fault diagnosis based on wavelet packet for fault feature extraction has been proposed for gear fault detection and diagnosis. First, this paper analyzes the variations of gear fault vibration signal, using time-domain and frequency-domain sign attributes to characterize these gear vibration signal and then extract fault sign attributes by using wavelet packet. This paper introduces a kind of new method for wavelet denoise, eliminating the problem of wavelet de-noise decompose level and de-noise threshold value selection, at the same time analysis a kind of wavelet packet transform method, eliminating the frequency and frequency band confusion, reducing the error in fault sign attribute extraction. At last, using fault simulation platform to simulate different conditions and different gear fault vibration signals. The results demonstrate that this method can accurately and reliably detect failure modes in a gearbox.

Original languageEnglish
Title of host publicationPractical Applications of Intelligent Systems - Proceedings of the 8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
EditorsZhenkun Wen, Tianrui Li
PublisherSpringer Verlag
Pages155-165
Number of pages11
ISBN (Electronic)9783642549267
DOIs
StatePublished - 2014
Externally publishedYes
Event8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013 - Shenzhen, China
Duration: 20 Nov 201323 Nov 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume279
ISSN (Print)2194-5357

Conference

Conference8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
Country/TerritoryChina
CityShenzhen
Period20/11/1323/11/13

Keywords

  • Fault diagnosis
  • Frequency aliasing
  • Wavelet packet

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