For the newly manufactured gearbox, it is essential to identify the presence of defects for industries. It is found that the defects in the newly manufactured gearbox are identified by running it with a motor. Based on the sound coming from the gearbox, the inspector takes a decision about the presence of faults in the gearbox. There are many faults in the gearbox such as shaft assembly errors, profile errors, burrs, and dents on the gear teeth. This paper discusses the methodology developed for the real-time fault identification of the gearbox using the LabVIEW virtual instrumentation in real-time mode and the supervised artificial intelligence technique already trained in another programming language. The Artificial Neural Network (ANN) and Radial Basis Function Neural Network (RBFNN) are used for identifying faults. The Virtual Instrumentation (VI) is developed with different colour indicators designed to indicate a specific fault and this indicator glows when the vibration signal is acquired from the particular fault.


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    Titel :

    Development of Real-Time Fault Diagnosis Technique for the Newly Manufactured Gearbox


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Sharma, Sanjay (Herausgeber:in) / Subudhi, Bidyadhar (Herausgeber:in) / Sahu, Umesh Kumar (Herausgeber:in) / Kane, Prasad V. (Autor:in)

    Kongress:

    International Conference on Robotics, Control, Automation and Artificial Intelligence ; 2022 November 24, 2022 - November 26, 2022



    Erscheinungsdatum :

    2023-11-18


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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