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    An Investigation Into Bearing Fault Diagnostics for Condition Based Maintenance Using Band - Pass Filtering and Wavelet Decomposition Analysis of Vibration Signals

    Access Status
    Fulltext not available
    Authors
    Wood, J.
    Mazhar, M.
    Howard, Ian
    Date
    2016
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Wood, J. and Mazhar, M. and Howard, I. 2016. An Investigation Into Bearing Fault Diagnostics for Condition Based Maintenance Using Band - Pass Filtering and Wavelet Decomposition Analysis of Vibration Signals, pp. 2049-2060.
    Source Title
    Proceedings of the International Conference on Industrial Engineering and Operations Management
    ISBN
    9780985549749
    School
    Department of Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/53860
    Collection
    • Curtin Research Publications
    Abstract

    © IEOM Society International.Rotating machines are essential assets in many industries, and critical to the operation of these machines is the health of the rolling element bearings used to support shafts and gears. Condition based maintenance programs allow the health of machine components to be determined, and repairs scheduled at the optimum time, and prior to unexpected failure. One of the most common methods for detecting rolling element bearing faults is vibration analysis, with a number of different techniques available. This analysis compares the fault detection ability of a spectral kurtosis optimized band - pass filter analysis technique with an energy level optimized wavelet decomposition analysis, and presents a basic semi - automated process for diagnosis. Wavelet analysis proved superior in its ability to detect both localized faults and extended outer race faults, whilst band - pass filtering was limited by its lack of time-frequency resolution. The semi-automated process utilized wavelet analysis and proved successful in detecting localized bearing faults. © IEOM Society International.

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