This paper presents an efficient algorithm for diagnosing the transmission faults using analytical techniques. An on-site dataset is used in this work. Statistical tools have been adapted to determine the feature set extracted from line current Perk’s vector modulus. Fuzzy logic is incorporated for the classification of faulty and healthy conditions. From the confusion matrix, it is proven that this algorithm has been proven to be accurate as it results accurate values in almost all the cases (>95%).


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    Titel :

    A Statistical Feature-Based Transmission Fault Identification and Classification


    Beteiligte:


    Erscheinungsdatum :

    04.08.2022


    Format / Umfang :

    2181208 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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