After a system is designed and installed its fault-diagnosis and subsequent maintenance becomes an important factor during its entire service life. The modern tendency in this realm is to employ some form of condition based maintenance strategy. This paper discusses such a diagnostic and maintenance methodology, which is based on the application of artificial neural networks. The monitoring strategy employs a two tier structure, which first identifies the abnormal behaviour and then analyses the sensed data in order to identify the behaviour and then analyses the sensed data in order to identify the possible fault. As an example, a turbo-charged diesel engine is employed to demonstrate the underlying principles. The monitoring system is designed to act as a computerised engineering expert, which utilises the routine-data to categorise the operational routines of the engine, and provides information for engine trouble shooting.


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    Title :

    Fault diagnosis of automotive engines using artificial neural networks


    Additional title:

    Fehlerdiagnose an Automotoven mit Hilfe von künstlichen neuralen Netzen


    Contributors:
    Javed, M.A. (author) / Sadek, H.R.M. (author) / Hope, A.D. (author)


    Publication date :

    1993


    Size :

    8 Seiten, 3 Bilder, 1 Tabelle, 6 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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