Bearing defect detection and diagnosis using a time encoded signal processing and pattern recognition method

S. Abdusslam, P. Raharjo, F. Gu, A. Ball

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Many new bearing monitoring and diagnosis methods have been explored in the last two decades to provide a technique that is capable of picking up an incipient bearing fault. Vibration analysis is a commonly used condition monitoring technique in world industry and has proved an effective method for rolling bearing monitoring systems. The focus of this paper is to combine two conventional methods: wavelet transform and envelope analysis with the Time Encoded Signal Processing and Recognition (TESPAR) to develop a better technique for detection of small bearing faults. Results show that TESPAR with these two combinations provides good fault discrimination in terms of location and severity for different bearing conditions.

LanguageEnglish
Article number012036
JournalJournal of Physics: Conference Series
Volume364
Issue number1
DOIs
Publication statusPublished - 2012
Event25th International Congress on Condition Monitoring and Diagnostic Engineering: Sustained Prosperity through Proactive Monitoring, Diagnosis and Management - University of Huddersfield, Huddersfield, United Kingdom
Duration: 18 Jun 201220 Jun 2012
Conference number: 25
http://compeng.hud.ac.uk/comadem2012/ (Link to Conference Website )

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time signals
pattern recognition
signal processing
defects
wavelet analysis
discrimination
envelopes
industries
vibration

Cite this

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Bearing defect detection and diagnosis using a time encoded signal processing and pattern recognition method. / Abdusslam, S.; Raharjo, P.; Gu, F.; Ball, A.

In: Journal of Physics: Conference Series, Vol. 364, No. 1, 012036, 2012.

Research output: Contribution to journalArticle

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