Aim to address the problem of low performance in existing gas leakage detection methods, an improved model based on MobileNetV3 is proposed. The transfer learning technique is used to train the improved model with a dataset of spectrograms generated from leaking audio. Comparative experiments show that the improved MobileNetV3 network model performs better than the MobileNetV3, VGG-16, and AlexNet network models in gas leak fault detection tasks. It also demonstrates that using the improved MobileNetV3 network model for gas leak fault detection has some usability.


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    Title :

    Gas Leak Fault Detection based on Improved MobileNetV3


    Contributors:
    Liu, Ping (author) / Xu, Yanwu (author) / Wang, Yingming (author) / Yu, Yongsheng (author)


    Publication date :

    2023-08-04


    Size :

    1691518 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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