Gear drives are considered as the most effective transmission method in automobiles as well as in various industries because of its high efficiency, reliability and high velocity ratio. As a result, from its trustful usage, failure in any part may lead to a large and unpredictable production loss along with massive service cost and safety concerns. Scheduled condition monitoring and Periodic maintenance are the only solution to avoid the above scenario. Vibration analysis is the most sounded term in fault detection due to its runtime condition monitoring and low cost. Nowadays, vibration analysis has been offset to the machine learning methods, which is a modern technique enabling us to automate such that the system can learn from the input data and make decisions with a nominal human interface whereas conventional methods are highly operator dependent. Here in this study, the effectiveness of a machine learning based gear fault diagnosis system is carried out. Gear defects like misalignment and broken teeth were considered. No combinations of these defects were considered. The experimental setup consists of a paired spur gear shafts, driven by a variable speed motor with a belt drive along with a vibrational data acquisition system. Vibration signals for three classes were collected including the signals from healthy gear too. TensorFlow is used to implement machine learning models. The proposed method is successful in detecting gear defects while the machine is in running condition. The new method is fast and can be automated. This reduces the human intervention to a minimum level


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Vibration Analysis of Gear Defects using Machine Learning Approach


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility ; 2021



    Erscheinungsdatum :

    2021-10-01




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Gear diagnostics using laser vibration analysis

    Watts,R.J. / Forbush,D. / US Army Tank Automotive Commando,TACOM,US | Kraftfahrwesen | 1989


    Steering Gear Control System using Machine Learning

    Europäisches Patentamt | 2024

    Freier Zugriff

    Torsional vibration analysis of the gear transmission system of high-speed trains with wheel defects

    Wang, Zhiwei / Cheng, Yao / Mei, Guiming et al. | SAGE Publications | 2020


    Research on the Rotation Vibration in the Transmission with Gear Box Defects

    Bogdevičius, Paulius / Bogdevičius, Marijonas / Prentkovskis, Olegas | Springer Verlag | 2020


    Research on the Rotation Vibration in the Transmission with Gear Box Defects

    Bogdevičius, Paulius / Bogdevičius, Marijonas / Prentkovskis, Olegas | TIBKAT | 2020