This paper presents a neural network system-GTNN for identifying the gapping of the main journal bearing of engines. Calculation results are compared with the experiment data, and the error of them is acceptable. Finally the explanation of the calculation result is given.


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    Titel :

    Neural network identifying system for the gapping of main journal bearing of engine


    Beteiligte:
    Jiang Xuejun (Autor:in) / Tang Fei (Autor:in) / Li Zhimin (Autor:in) / Qi Baohui (Autor:in)


    Erscheinungsdatum :

    01.01.1999


    Format / Umfang :

    278475 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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