Bearing fault diagnosis using time encoded signal processing and recognition

Shukri A. Abdusslam, F. Gu, A. Ball

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

1 Citation (Scopus)

Abstract

Many novel condition monitoring techniques have been invented in recent yearsand the challenge lies in coming up with a highly reliable and cost efficient monitoring system which should be capable of tracking down and give an early indication of machinery's faults. The focus of this paper is to develop advanced approaches based on advanced intelligent computations to diagnosis and prognosis bearing condition. TESPAR (Time Encoded Signal Processing and Recognition) is an effective and direct way for describing complex waveforms in digital terms. It is the generic terms set to a collection of novel signal analysis, recognition and classification approaches that can be applied to describe and classify various ranges of complicated band limited signals. The results show that vibration signal waveforms of bearing faults can be digitized and analyzed in terms of its epochs' duration and shape which are the main parameters of the TESPAR technique that provides an accurate separation between different bearing faults with different degree of severity.

Original languageEnglish
Title of host publication7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010, CM 2010/MFPT 2010
PublisherBritish Institute of Non-Destructive Testing
Pages197-205
Number of pages9
Volume1
ISBN (Print)9781618390134
Publication statusPublished - 22 Jun 2010
Event7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies - Stratford-upon-Avon, United Kingdom
Duration: 22 Jun 201024 Jun 2010
Conference number: 7

Conference

Conference7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies
Abbreviated titleCM/MFPT 2010
CountryUnited Kingdom
CityStratford-upon-Avon
Period22/06/1024/06/10

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Abdusslam, S. A., Gu, F., & Ball, A. (2010). Bearing fault diagnosis using time encoded signal processing and recognition. In 7th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2010, CM 2010/MFPT 2010 (Vol. 1, pp. 197-205). British Institute of Non-Destructive Testing.