Recognition of leakage aperture of natural gas pipeline based on compression sensing and convolution network

WEN Jiangtao1, FU Lei1, SUN Jiedi2,3, WANG Tao1, ZHANG Guangyu1, ZHANG Pengcheng1

Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (21) : 17-23.

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PDF(1967 KB)
Journal of Vibration and Shock ›› 2020, Vol. 39 ›› Issue (21) : 17-23.

Recognition of leakage aperture of natural gas pipeline based on compression sensing and convolution network

  • WEN Jiangtao1, FU Lei1, SUN Jiedi2,3, WANG Tao1, ZHANG Guangyu1, ZHANG Pengcheng1
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Abstract

Aiming at problems of large redundancy of raw data, strong subjectivity dependence of feature selection and low recognition accuracy under complex environment for traditional natural gas pipeline leakage aperture recognition, a leakage aperture recognition method based on compression sensing and 1-D convolution network was proposed.Firstly, the random Gaussian matrix was used to do compression collection of original leakage signals, and the full leakage information was obtained with less compression sensing domain data.Then, a deep 1-D convolutional network was constructed, and the compression collection data were fed into the network to realize adaptive feature extraction and leakage aperture recognition with high accuracy.Finally, effects of the main parameters on recognition results were analyzed.Test results showed that the proposed method can quickly and accurately realize the leakage aperture identification of natural gas pipelines; it has better robustness under low SNR environment; its overall recognition effect is superior to that of the traditional classification method.

Key words

pipeline leakage aperture recognition / compression sensing collection / 1-D convolutional network / adaptive feature extraction

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WEN Jiangtao1, FU Lei1, SUN Jiedi2,3, WANG Tao1, ZHANG Guangyu1, ZHANG Pengcheng1. Recognition of leakage aperture of natural gas pipeline based on compression sensing and convolution network[J]. Journal of Vibration and Shock, 2020, 39(21): 17-23

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