基于光纤传感的管道清管检测器智能定位与跟踪

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中图分类号：TE832 文献标识码：ADOI：10.12473/CPM.202410034

Intelligent Positioning and Tracking of Pipeline Pig Detector Based on Fiber-Optic Sensing

Zhang Taojia1Zhang Haifeng2，3Yan Bingchuan1Song Bohan²Ji Yuling²Li Jiangbo²Wu Qiong4 （1.PipeChinaStorage&TransportationTechnologyCompany；2.SchoolofInformationandControlEngineering，iaoinget rochemicalUniversity；3.EnergyOpticalSensingandSafetyR&DCenter，ResearchInstituteofTsinghua UniversityinShenzhen; 4.PipeChina Northeast Pipeline Company）

Abstract：To monitor themotion position of pigdetector inalong-distance oil andgas pipeline in real time and detectthe stuck pig incident intime，an inteligent positioning and tracking technology of pipeline pig detector was proposed. The redundant optical fibers in the communication optical cable accompanying the pipeline were used to construct a distributed optical fiber vibration sensing system.The frame-based energy feature extraction technology wasused to obtain the unique inverted“V”-shaped energy feature signal generated by the contact between the pig detector and the pipeline welded seam during the operation of the pig detector.Based on a twodimensionalconvolutional neural network，alightweight inteligent recognition modelfor thepig detector was constructed，anditseffectiveness was experimentallvalidatedduring thepigdetectionoperationof TianjinPort-Huabei Petrochemical CrudeOil Pipeline.The test results show that the proposed intellgent positioning and tracking technology enables visualization of movement trajectory of the pig detector along the entire 40km pipeline，achieving a recognition accuracy of 93% . This technology provides a cutting-edge solution for achieving real-time unmanned intelligent positioning and tracking of pig detector during itsoperation in long-distance oil and gas pipelines.

Keywords：long-distance oilandgab pipeline;pig detector；distributed fiber-optic sensing；vibration sensing；convolutional neural network（CNN）；location recognition

0 引言

石油天然气长输管道是石油天然气工业中的重要组成部分，为了保障其正常运行和安全生产，需要定期进行清管和检测作业[1-2]。（剩余8906字）