DOI QR코드

DOI QR Code

Research on Damage Identification of Buried Pipeline Based on Fiber Optic Vibration Signal

  • Weihong Lin (College of Communication and Art Design, University of Shanghai for Science and Technology) ;
  • Wei Peng (CSSC Survey, Design and Research Institute Co., Ltd.) ;
  • Yong Kong (School of Electronic and Electrical Engineering, Shanghai University of Engineering Science) ;
  • Zimin Shen (College of Communication and Art Design, University of Shanghai for Science and Technology) ;
  • Yuzhou Du (College of Communication and Art Design, University of Shanghai for Science and Technology) ;
  • Leihong Zhang (School of Optical-electrical and Computer Engineering, University of Shanghai for Science and Technology) ;
  • Dawei Zhang (School of Optical-electrical and Computer Engineering, University of Shanghai for Science and Technology)
  • 투고 : 2023.04.20
  • 심사 : 2023.07.24
  • 발행 : 2023.10.25

초록

Pipelines play an important role in urban water supply and drainage, oil and gas transmission, etc. This paper presents a technique for pattern recognition of fiber optic vibration signals collected by a distributed vibration sensing (DVS) system using a deep learning residual network (ResNet). The optical fiber is laid on the pipeline, and the signal is collected by the DVS system and converted into a 64 × 64 single-channel grayscale image. The grayscale image is input into the ResNet to extract features, and finally the K-nearest-neighbors (KNN) algorithm is used to achieve the classification and recognition of pipeline damage.

키워드

과제정보

The authors acknowledge the support given by the National Natural Science Foundation of China (Grant No. 62275153, 61875125, 62005165) and the development fund for Shanghai talents (Grant No. 2021005). In addition, the authors want to express appreciation for the editor and anonymous reviewers for their valuable comments and suggestions for this paper.

참고문헌

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