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Diagnostic Feature Development based on Dynamic Time Warping of Dynamic Signals under Variable Machine Operating Condition

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Zhen, Dong, James, Gu, Tie, Wang, Fengshou, Gu and Ball, Andrew (2010) Diagnostic Feature Development based on Dynamic Time Warping of Dynamic Signals under Variable Machine Operating Condition. In: CM 2010 and MFPT 2010 : The Seventh International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 22-24 June 2010, Stratford-upon-Avon, UK.

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    Abstract

    In condition monitoring (CM), measurements are often taken when a machine runs under different loads and speeds. The signals in these conditions show similar profiles but do not line up in time-axis for adequate comparison. Detection features derived in the time domain are not accurate enough to discriminate small changes in machine health conditions. In this paper, a Dynamic Time Warping Algorithm (DTW) is explored in aligning the signals under different machine operating conditions for both normal and faulty status. The feature and performance of DTW algorithms are reviewed and improved based on a set of simulated data consisting of common features in CM practice. Experimental data sets of electrical motor current signals have been studied using DTW. The performance of the event alignment is evaluated by the capability in detecting the fault with different severities. Preliminary results show the aligned data produces accurate results and hence can lead to better detection and diagnosis results.

    Item Type: Conference or Workshop Item (Speech)
    Uncontrolled Keywords: Digital Signal Processing and Imaging, Signal processing, Data processing, Vibration analysis
    Subjects: T Technology > TJ Mechanical engineering and machinery
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Automotive Engineering Research Group
    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
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    References:

    1. E.Peter and P. Fanning, 'Vibration Based Conditon Monitoring: A Review.' Structural Health Monitoring, 2004.
    2. Friswell, M. and J.E.T. Penny, 'Is damage location using vibration measurements practical?' Structural Damage Assessment Using Advanced Signal Processing Procedures, 1997: p. pp.351-362.
    3. Henniger, O. and S. Muller, 'Effects of time normalization on the accuracy of Dynamic Time Warping'.
    4. Strle, B., M. Mozina, and I. Bratko, 'Qualitative approximation to Dynamic Time Warping similarity between time series data'.
    5. Ko, M.H., et al., 'Using dynamic time warping for online temporal fusion in multisensor systems'. Information Fusion, 2008. 9(3): p. 370-388.
    6. J.Keogh, E. and M. J.Pazzani, 'Derivative Dynamic Time Warping'.
    7. Tormene, P., et al., 'Matching incomplete time series with dynamic time warping: an algorithm and an application to post-stroke rehabilitation'. Artificial Intelligence in Medicine, 2009. 45(1): p. 11-34.
    8. He, Q., Z. Feng, and F. Kong, 'Detection of signal transients using independent component analysis and its application in gearbox condition monitoring'. Mechanical Systems and Signal Processing, 2007. 21(5): p. 2056-2071.
    9. M. E. H. Benbouzid, 'A review of induction motors signature analysis as a medium for faults detection', IEEE Trans. Ind. Elec., Vol. 47, No. 5, Oct. 2000, pp 984-993.
    10. R. R. Obaid, T. G. habetler, R. M. Tallam, 'Detecting load unbalance and shaft misalignment using stator current in inverter-driven induction motors', IEEE int. Elec. Mach. And Drives Conf., pp1454-1458, 2003.

    Depositing User: Dong Zhen
    Date Deposited: 03 Aug 2010 12:28
    Last Modified: 20 Jun 2011 17:43
    URI: http://eprints.hud.ac.uk/id/eprint/8189

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