Abstract As a statistical model of time series, the hidden Markov model (HMM) is suitable for the dynamic time series analysis, especially for the signal with a large amount of information and nonstationary and low reproducibility. It is a dynamic pattern recognition tool, which could gather statistic models, classify the information of a time span, and expand the fault diagnosis method which is only based on the static observation.


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    Title :

    Fault Diagnosis Method Based on Hidden Markov Model


    Contributors:
    Zhang, Wei (author)


    Publication date :

    2016-01-01


    Size :

    27 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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