The paper considers the problem of implementing a practical approach to predictive maintenance (maintenance based on the actual technical condition). With this type of service, the state of the system is analyzed continuously or periodically. Based on the data obtained, a forecast of the technical condition of the equipment for a certain period of time is carried out, programs and maintenance plans are formed and, if necessary, adjusted. The aim of the work is to develop a generalized approach to building a predictive service system based on data of some complex technical object, collected by the SCADA system, with their further processing using computer modeling and machine learning methods. Implementation of this approach minimizes the likelihood of an unplanned system shutdown.


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    Titel :

    Technical Diagnostics of Equipment Using Data Mining Technologies


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Bieliatynskyi, Andrii (Herausgeber:in) / Breskich, Vera (Herausgeber:in) / Tsarkova, Evgeniya (Autor:in) / Belyaev, Alexander (Autor:in) / Lagutin, Yaroslav (Autor:in) / Andreeva, Elena (Autor:in) / Matveev, Yuri (Autor:in)


    Erscheinungsdatum :

    2021-11-02


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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