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    A Copula-based Sampling Method for Data-driven prognostics and health management

    Date
    2013-06-24
    Author
    Xi, Zhimin
    Jing, Rong
    Wang, Pingfeng
    Hu, Chao
    Metadata
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    Citation
    Zhimin Xi; Rong Jing; Pingfeng Wang; Chao Hu, "A Copula-based sampling method for data-driven prognostics and health management," in Prognostics and Health Management (PHM), 2013 IEEE Conference on , vol., no., pp.1-10, 24-27 June 2013
    Abstract
    This paper develops a Copula-based sampling method for data-driven prognostics and health management (PHM). The principal idea is to first build statistical relationship between failure time and the time realizations at specified degradation levels on the basis of off-line training data sets, then identify possible failure times for on-line testing units based on the constructed statistical model and available on-line testing data. Specifically, three technical components are proposed to implement the methodology. First of all, a generic health index system is proposed to represent the health degradation of engineering systems. Next, a Copula-based modeling is proposed to build statistical relationship between failure time and the time realizations at specified degradation levels. Finally, a sampling approach is proposed to estimate the failure time and remaining useful life (RUL) of on-line testing units. Two case studies, including a bearing system in electric cooling fans and a 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology.
    Description
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    URI
    http://dx.doi.org/10.1109/ICPHM.2013.6621450
    http://hdl.handle.net/10057/11574
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