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    Volume 49, Issue 2 (June 2019)

    New Gear Fault Diagnosis Method Based on MODWPT and Neural Network for Feature Extraction and Classification

    (Received 12 February 2019; accepted 16 April 2019)

    Published Online: 14 June 2019

    CODEN: JTEVAB

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    Abstract

    Gear fault diagnosis using vibration signals has become the subject of intensive studies to detect any sudden failure. However, these signals exhibit nonlinear and nonstationary behaviors when the rotating machine operates under multiple working conditions. Furthermore, fault features extraction and classification of multiple gear states are always unsatisfactory and considered as a huge task. This is the main reason that motivates us to develop a new intelligent gear fault diagnosis method in order to automatically identify and classify several kinds of gear defects under different work conditions. So in this article, we propose a combination between the maximal overlap discrete wavelet packet transform (MODWPT), entropy indicator, and a multilayer perceptron (MLP) neural network as a new automatic fault diagnosis approach. MODWPT decomposes the data signal into several components using a uniform frequency bandwidth. Each decomposed component is selected to extract feature vector using entropy indicator. Finally, MLP provides a powerful automatic tool for identifying and classifying the aforementioned extracted features. Experimental vibration signals of healthy gear; gear with general surface wear; gear with chipped tooth in length; gear with chipped tooth in width; gear with missing tooth; and gear with tooth root crack are recorded under fifteen different work conditions to test the effectiveness of the suggested technique. Experimental results affirm that our proposed approach can successfully detect, identify, and classify the gear fault pattern in all cases.

    Author Information:

    Afia, Adel
    Department of Mechanical Engineering, Solid Mechanics and Systems Laboratory (LMSS), University M’hamed Bougara Boumerdès, Boumerdès,

    Rahmoune, Chemseddine
    Department of Mechanical Engineering, Solid Mechanics and Systems Laboratory (LMSS), University M’hamed Bougara Boumerdès, Boumerdès,

    Benazzouz, Djamel
    Department of Mechanical Engineering, Solid Mechanics and Systems Laboratory (LMSS), University M’hamed Bougara Boumerdès, Boumerdès,

    Merainani, Boualem
    Department of Mechanical Engineering, Solid Mechanics and Systems Laboratory (LMSS), University M’hamed Bougara Boumerdès, Boumerdès,

    Fedala, Semcheddine
    Applied Precision Mechanics Laboratory, Institute of Optics and Precision Mechanics, Setif University, Setif,


    Stock #: JTE20190107

    ISSN:0090-3973

    DOI: 10.1520/JTE20190107

    Author
    Title New Gear Fault Diagnosis Method Based on MODWPT and Neural Network for Feature Extraction and Classification
    Symposium ,
    Committee F24