夏彦卫, 贾伯岩, 庞先海, 丁立坤, 王怡欣. 基于BOTDR分布式检测技术的光缆隐蔽性缺陷识别[J]. 应用光学, 2024, 45(1): 229-236. DOI: 10.5768/JAO202445.0108002
引用本文: 夏彦卫, 贾伯岩, 庞先海, 丁立坤, 王怡欣. 基于BOTDR分布式检测技术的光缆隐蔽性缺陷识别[J]. 应用光学, 2024, 45(1): 229-236. DOI: 10.5768/JAO202445.0108002
XIA Yanwei, JIA Boyan, PANG Xianhai, DING Likun, WANG Yixin. Identification of hidden defects in optical cables based on BOTDR distributed detection technology[J]. Journal of Applied Optics, 2024, 45(1): 229-236. DOI: 10.5768/JAO202445.0108002
Citation: XIA Yanwei, JIA Boyan, PANG Xianhai, DING Likun, WANG Yixin. Identification of hidden defects in optical cables based on BOTDR distributed detection technology[J]. Journal of Applied Optics, 2024, 45(1): 229-236. DOI: 10.5768/JAO202445.0108002

基于BOTDR分布式检测技术的光缆隐蔽性缺陷识别

Identification of hidden defects in optical cables based on BOTDR distributed detection technology

  • 摘要: 提出基于布里渊光时域反射(Brillouin optic time domain reflectometer,BOTDR)分布式检测技术与解调信号的光缆隐蔽性缺陷识别方法,识别检测光缆隐蔽性缺陷。在生产阶段将光纤植入多股碳纤维导线复合芯内部作为传感器,依据BOTDR技术与光时域反射(optic time domain reflectometer,OTDR)技术原理,构建关于碳纤维导线光缆隐蔽性检测的分布式传感系统,利用光纤对温度、应力、传播损耗的高精度感知,多维度地分析碳纤维导线光缆的隐蔽性缺陷及位置分布,实现光缆的隐蔽性缺陷识别。利用morlet小波解调布里渊散射信号,提取包络信息,去除信号噪声,采用列文伯格-马夸尔特算法,拟合布里渊散射谱数据,精确估计最优Brillouin频移量参数,提升整体缺陷识别精度。实验证明:该方法可以准确地对光缆的隐蔽性缺陷进行表征,实现多股碳纤维导线光缆隐蔽性缺陷的快速、有效识别,促进碳纤维导线光缆更好地应用于增容、大跨越等工程中。

     

    Abstract: A method for identifying and measuring the hidden defects of optical cables based on Brillouin optic time domain reflectometer (BOTDR) distributed detection technology and demodulated signals was proposed to identify and measure the hidden defects of optical cables and ensure the safe operation of multi-strand carbon fiber optic cables used in projects such as capacity expansion and large span. In the production stage, the optical fiber was embedded in the composite core of multi-strand carbon fiber cable as a sensor. According to the principle of BOTDR technology and optic time domain reflectometer (OTDR) technology, a distributed sensing system for the detection of the hidden defects of carbon fiber cable was constructed. The hidden defects and position distribution of carbon fiber cable were analyzed in a multi-dimensional way by using the high-precision sensing of the optical fiber on temperature, stress and propagation loss, which realized hidden defect identification of optical cable. The Morlet wavelet was used to demodulate Brillouin scattering signal, extract envelope information and remove signal noise. Levenberg-Marquardt algorithm was used to fit Brillouin scattering spectrum data, accurately estimate the optimal Brillouin frequency shift parameter, and improve the overall defect recognition accuracy. The experimental results show that this method can accurately characterize the hidden defects of optical cable, realize the fast and effective identification of hidden defects of multi-strand carbon fiber cable, and promote the better application of carbon fiber cable in capacity expansion, large span and other projects.

     

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