Laser & Optoelectronics Progress, Volume. 61, Issue 17, 1706002(2024)

Φ-OTDR Localization Method Based on Region Segmentation and Edge Detection

Wei Shen1, Jingyi Dai2, Yong Dai1, Xin Hu1, Ling Ju1, Xinglong Wang1, Chuanlu Deng2, and Yi Huang2、*
Author Affiliations
  • 1State Grid Taizhou Power Supply Company, Taizhou 225300, Jiangsu, China
  • 2Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, China
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    In response to the large amount of data processing in phase-sensitive optical time-domain reflection (Φ-OTDR) technology for disturbance localization, a positioning method combining region segmentation and edge detection is proposed. The fast coarse localization of the disturbance occurrence region is achieved by dividing the optical fiber into segments, followed by fine localization using an edge detection algorithm based on the Sobel operator within the disturbance region. A heterodyne coherent Φ-OTDR system is employed for data acquisition in the experiments to localize three types of disturbance events on a 5 km sensing fiber. The results show that the coarse positioning method based on region segmentation enhances the system's ability to locate disturbances in noise. The average processing time for each sample is only 0.046 s, which is an order of magnitude lower than that of the traditional method. In addition, the proposed combined method improves real-time localization over using edge detection algorithm alone, while maintaining localization accuracy. The localization error is less than 2.84 m, indicating potential for application in accurately locating external disturbances in real-time systems.

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    Wei Shen, Jingyi Dai, Yong Dai, Xin Hu, Ling Ju, Xinglong Wang, Chuanlu Deng, Yi Huang. Φ-OTDR Localization Method Based on Region Segmentation and Edge Detection[J]. Laser & Optoelectronics Progress, 2024, 61(17): 1706002

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    Paper Information

    Category: Fiber Optics and Optical Communications

    Received: Oct. 13, 2023

    Accepted: Dec. 11, 2023

    Published Online: Sep. 14, 2024

    The Author Email: Yi Huang (huangyi1008@shu.edu.cn)

    DOI:10.3788/LOP232290

    CSTR:32186.14.LOP232290

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