Gearbox fault diagnosis under different operating conditions based on time synchronous average and ensemble empirical mode decomposition

Luyang Guan, Yimin Shao, Fengshou Gu, Bruno Fazenda, Andrew Ball

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

In this paper, a new method is proposed by combining ensemble empirical mode decomposition (EEMD) with order tracking techniques to analyse the vibration signals from a two stage helical gearbox. The method improves EEMD results in that it overcomes the potential deficiencies and achieves better order spectrum representation for fault diagnosis. Based on the analysis, a diagnostic feature is designed based on the order spectra of extracted IFMs for detection and separation of gearbox faults. Experimental results show this feature is sensitive to different fault severities and robust to the influences from operating conditions and remote sensor locations.

Original languageEnglish
Title of host publicationICCAS-SICE 2009
Subtitle of host publicationICROS-SICE International Joint Conference 2009
PublisherIEEE
Pages383-388
Number of pages6
ISBN (Electronic)9784907764333
ISBN (Print)9784907764340
Publication statusPublished - 13 Nov 2009
EventThe Society of Instrument and Control Engineers & The Institute of Control, Robotics and Systems International Joint Conference - International Congress Centre , Fukuoka, Japan
Duration: 18 Aug 200921 Aug 2009
http://www.sice.or.jp/org/sice2009/ (Link to Conference Website)

Conference

ConferenceThe Society of Instrument and Control Engineers & The Institute of Control, Robotics and Systems International Joint Conference
Abbreviated titleICROS-SICE 2009
CountryJapan
CityFukuoka
Period18/08/0921/08/09
Internet address

Fingerprint Dive into the research topics of 'Gearbox fault diagnosis under different operating conditions based on time synchronous average and ensemble empirical mode decomposition'. Together they form a unique fingerprint.

Cite this