Exploration and application of convolutional neural network to improve the quality of DAS voice print machine recognition and acoustic reduction

Liu Xin; Wenbo Shang; Shuanxiong Ma; Xiaoyan Li; Zhang Yan; Zhaodong Zhang

doi:10.1117/12.2602043

24 November 2021 Exploration and application of convolutional neural network to improve the quality of DAS voice print machine recognition and acoustic reduction

Liu Xin, Wenbo Shang, Shuanxiong Ma, Xiaoyan Li, Zhang Yan, Zhaodong Zhang

Author Affiliations +

Proceedings Volume 12061, AOPC 2021: Infrared Device and Infrared Technology; 120610A (2021) https://doi.org/10.1117/12.2602043
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

In order to solve the technical problems of distributed acoustic sensor(DAS)system in many kinds of acoustic signal recognition, In this paper, an implementation path of acoustic signal machine recognition technology is proposed, which realizes the voice print and acoustic wave restoration of DAS machine recognition, and improves the quality of recognition and restoration.. Methods by preprocessing the optical fiber signal caused by sound, including signal framing, windowing, short-time Fourier transform and signal enhancement, the signal was transformed into a spectrogram, and the convolution neural network (CNN) was used to train the 13400 datas collected from the scene to machine judge the four types of acoustic signals: mechanical excavation, manual operation, vehicle passing and gas leakage Type. According to 800 test datas, the accuracy, recall and F1 value of the model are 96.4%, 96.5% and 96.0% respectively, and the average recognition speed is 30s. The feasibility of CNN model to realize and improve the quality of DAS machine voice print recognition and acoustic reduction was verified by field tests.

Citation Download Citation

Liu Xin, Wenbo Shang, Shuanxiong Ma, Xiaoyan Li, Zhang Yan, and Zhaodong Zhang "Exploration and application of convolutional neural network to improve the quality of DAS voice print machine recognition and acoustic reduction", Proc. SPIE 12061, AOPC 2021: Infrared Device and Infrared Technology, 120610A (24 November 2021); https://doi.org/10.1117/12.2602043

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