In the course of acoustic diagnosis of multi-shaft drives on the basis of spur wheels, the diagnostician is faced with the problem of excessive saturation of the analyzed signal with various kinds of frequency components. Reducing the amount of data analyzed may result in the loss of important diagnostic information. Therefore, in order to make the diagnosticians work easier and at the same time maintain the accuracy of the diagnosed local damage to the gear tooth it is necessary to identify the list of informative frequency components. They should respond to the occurrence of this defect in the tooth-contact zone and have a sufficiently thoroughly studied mathematical framework that will make it possible to use methods of their automatic determination. The obtained digital image will allow using artificial neural network models for its processing.


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    Titel :

    Acoustic diagnostics of local damages of spur wheels in multi-shaft drive using neural network models


    Beteiligte:
    A. N. Parfiyevich (Autor:in) / A. V. Dragan (Autor:in) / V. A. Sokol (Autor:in)


    Erscheinungsdatum :

    2020




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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