Fault diagnosis for space testing and launching includes two major parts: fault diagnosis for testing and fault diagnosis for launching. This diagnosis for testing refers to testing, diagnosis, location, and troubleshooting for the launch vehicle based on testing data during unit testing, subsystem testing, and sum‐check testing. Fault diagnosis for launching supports security control analysis and decision‐making, analyzes the trend of parameters and working conditions based on telemetry data, diagnose abnormal situations, and conduct security assessment. This chapter analyzes the problem of fault diagnosis for space testing and launching, and discusses the development of intelligent fault diagnosis. It focuses on the combination of traditional fault diagnosis methods with intelligent ones such as the kernel principal component analysis (KPCA), multiscale principal component analysis (MSPCA), wavelet analysis, and ant colony algorithm. A malfunction diagnosis approach based on Hopfield neural network is also discussed in the chapter.


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    Titel :

    Intelligent Fault Diagnosis for Space Launch and Testing


    Beteiligte:
    Chai, Yi (Autor:in) / Li, Shangfu (Autor:in)


    Erscheinungsdatum :

    2015-11-06


    Format / Umfang :

    81 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch