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Remotely gear condition monitoring using traditional signal processing techniques

Al-Arbi, Salem, Gu, Fengshou, Guan, Luyang and Ball, Andrew (2009) Remotely gear condition monitoring using traditional signal processing techniques. In: Proceedings of Computing and Engineering Annual Researchers' Conference 2009: CEARC’09. University of Huddersfield, Huddersfield, pp. 111-117. ISBN 9781862180857

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    Abstract

    For gearbox condition monitoring, because the difficulty of sensor installation, it is a common practice to measure the vibration at a location far from the fault source. In addition operating the gearbox under different loads and speeds also produces the vibration signals with different components. The vibration measured in this way may be distorted significantly by the effect of signal transmission paths and the interference from other sources. The suppression of distortions is thus a key issue for the remote measurements based condition monitoring. In this paper, the influences of transducer locations and operating conditions on the vibration signal are investigated on a typical gearbox transmission system for the detection of the faults induced to the gearbox. The experimental study results show that the performance of traditional signal processing techniques is not sufficient to reveal fault detection information. However, the new feature from the spectrum of time synchronous average (TSA) signal is very effective in suppressing noise and hence leads to better detection of the local faults induced to the gear system.

    Item Type: Book Chapter
    Uncontrolled Keywords: Gearbox, attenuation, interference, traditional analysis
    Subjects: T Technology > T Technology (General)
    T Technology > TL Motor vehicles. Aeronautics. Astronautics
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
    School of Computing and Engineering > Diagnostic Engineering Research Centre
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Energy, Emissions and the Environment Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Machinery Condition and Performance Monitoring Research Group
    School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
    School of Computing and Engineering > High-Performance Intelligent Computing
    School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
    Related URLs:
    Depositing User: Sharon Beastall
    Date Deposited: 27 Jan 2010 13:51
    Last Modified: 08 Dec 2010 13:01
    URI: http://eprints.hud.ac.uk/id/eprint/6872

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