107 / 2021-03-30 15:53:58
Visual recognition method of air leaking signal based on convolutional neural network
Visualization of acoustic signals,CNN,Leaking detection,real-time
Draft Accepted
Li Wang / Wuhan University of Technology
Yongsheng Yu / Wuhan University of Technology
Ziqin Zhou / Wuhan University of Technology
Zhe Wang / Wuhan University of Technology
Peng Song / Wuhan University of Technology
Acoustic signal detection to achieve high accuracy and real-time performance has always been an important issue in the field of acoustics. Convolutional neural network is a new type of artificial neural network method that combines artificial neural network and deep learning technology, and has been widely used in the field of image recognition. In this paper, using the visualization of acoustic signals combined with image recognition methods of convolutional neural networks, an artificial intelligence-based gas leaking signal detection method is proposed.This method converts the acoustic signal into a spectrogram, and uses the convolutional neural network as the input to train, and obtains a gas leaking recognition model with high recognition accuracy. The experimental results show that the model can be accurate, reliable, and real-time online detection of whether there is a gas leaking.
Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

Sponsored By
Qingdao University of Technology