Ball bearing early fault detection using wavelet analysis

A. Al-Khalidy, D. Dragomir-Daescu

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

2 Scopus citations

Abstract

Detection of ball bearing faults has been for long time a great concern in the field of condition monitoring of machines. One of the standard methods used in industry is the vibration envelope method or High-Frequency Resonance Technique (HFRT). In the present work, wavelet transform is implemented in HFRT for detecting the fault signatures that are buried in mechanical and electro-magnetic induced vibration signals. Induction motor ball bearing vibration signals are filtered using Daubechies orthonormal wavelet family and the filtered signal is amplitude demodulated using a digital envelope. The spectrum of the signal envelope clearly identifies the incipient faults. The results obtained are superior to those using the classical HFRT because the signal to noise ratio is increased and therefore the ability and accuracy in detecting early failures are improved. The strength of this technique lies in its robustness to high background noise levels and its virtual independence on the mechanical carrier frequencies. In this way the need for band pass filters centered on resonant structural frequencies is eliminated. This paper presents the results of an experimental study performed on induction motors ball bearings in the presence of an overwhelming electro-magnetic noise, and with limited access to bearing housing.

Original languageEnglish (US)
Title of host publicationStructural Health Monitoring 2003
Subtitle of host publicationFrom Diagnostics and Prognostics to Structural Health Management - Proceedings of the 4th International Workshop on Structural Health Monitoring, IWSHM 2003
EditorsFu-Kuo Chang
PublisherDEStech Publications
Pages541-549
Number of pages9
ISBN (Electronic)1932078207, 9781932078206
StatePublished - Jan 1 2003
Event4th International Workshop on Structural Health Monitoring: From Diagnostics and Prognostics to Structural Health Management, IWSHM 2003 - Stanford, United States
Duration: Sep 15 2003Sep 17 2003

Publication series

NameStructural Health Monitoring 2003: From Diagnostics and Prognostics to Structural Health Management - Proceedings of the 4th International Workshop on Structural Health Monitoring, IWSHM 2003

Other

Other4th International Workshop on Structural Health Monitoring: From Diagnostics and Prognostics to Structural Health Management, IWSHM 2003
CountryUnited States
CityStanford
Period9/15/039/17/03

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Information Management

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  • Cite this

    Al-Khalidy, A., & Dragomir-Daescu, D. (2003). Ball bearing early fault detection using wavelet analysis. In F-K. Chang (Ed.), Structural Health Monitoring 2003: From Diagnostics and Prognostics to Structural Health Management - Proceedings of the 4th International Workshop on Structural Health Monitoring, IWSHM 2003 (pp. 541-549). (Structural Health Monitoring 2003: From Diagnostics and Prognostics to Structural Health Management - Proceedings of the 4th International Workshop on Structural Health Monitoring, IWSHM 2003). DEStech Publications.