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

被引：2

作者：

Lin, Weihong ^{[1
]}

Peng, Wei ^{[3
]}

Kong, Yong ^{[2
]}

Shen, Zimin ^{[1
]}

Du, Yuzhou ^{[1
]}

Zhang, Leihong ^{[4
]}

Zhang, Dawei ^{[4
]}

机构：

[1] Univ Shanghai Sci & Technol, Coll Commun & Art Design, Shanghai 200093, Peoples R China

[2] Shanghai Univ Engn Sci, Sch Elect & Elect Engn, Shanghai 201620, Peoples R China

[3] CSSC Survey Design & Res Inst Co Ltd, Shanghai, Peoples R China

[4] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai 200093, Peoples R China

来源：

CURRENT OPTICS AND PHOTONICS | 2023年 / 7卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Distributed fiber optic vibration sensing; Pattern recognition; Residual network; RECOGNITION;

D O I：

10.3807/COPP.2023.7.5.511

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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 x 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.

引用

页码：511 / 517

页数：7

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