基于DAS探测的动态缆紧固状态监测研究

孙红军; 郭诗然; 蒋雪蕾; 安博文; 陈元林; 王庆松

doi:10.13756/j.gtxyj.2025.240089

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基于DAS探测的动态缆紧固状态监测研究

光纤光缆技术与应用 | 更新时间：2025-10-15

- 基于DAS探测的动态缆紧固状态监测研究
- Research on Dynamic Cable Fastening State Monitoring based on Distributed Acoustic Sensor Detection
- 光通信研究 2025年第5期
- 作者机构：
  
  1.中海油融风能源有限公司，上海　200335
  2.上海海事大学　信息工程学院，上海　201306
- 作者简介：
  
  孙红军（1981-），男，安徽池州人。高级工程师，学士，主要研究方向为新能源应用。
  蒋雪蕾，助理工程师。E-mail：2463578923@qq.com
- 基金信息：
- DOI：10.13756/j.gtxyj.2025.240089
  中图分类号： TN818
- 收稿：2024-05-06，
  
  修回：2024-05-13，
  
  纸质出版：2025-10-10
- 稿件说明：
移动端阅览
孙红军，郭诗然，蒋雪蕾，等. 基于DAS探测的动态缆紧固状态监测研究[J]. 光通信研究，2025(5): 240089.

Sun H J, Guo S R, Jiang X L, et al. Research on Dynamic Cable Fastening State Monitoring based on Distributed Acoustic Sensor Detection[J]. Study on Optical Communications, 2025(5): 240089.
孙红军，郭诗然，蒋雪蕾，等. 基于DAS探测的动态缆紧固状态监测研究[J]. 光通信研究，2025(5): 240089. DOI： 10.13756/j.gtxyj.2025.240089.

Sun H J, Guo S R, Jiang X L, et al. Research on Dynamic Cable Fastening State Monitoring based on Distributed Acoustic Sensor Detection[J]. Study on Optical Communications, 2025(5): 240089. DOI： 10.13756/j.gtxyj.2025.240089.

摘要

【目的】

深远海浮式风机的动态缆从海面入海直至敷埋于海床，动态缆的可靠性对于浮式风机的安全稳定运行至关重要。文章针对动态缆紧固点的监控难题，提出了一种有效的解决方案，并验证了其在实际应用中的效果。

【方法】

为了实现这一目标，采用分布式光纤测温和声波探测技术，以获取动态缆沿线的温度和扰动信息，这些数据为后续的分析和处理提供了基础；利用沿线温度特征实现了监测点的空间定位，将浮式风机上弯点、浮筒点和锚链点确定为重点监测位置；对这些监测点的频域特征进行分析和识别，结果显示，3个监测点之间相互识别率达到91%；最终，基于训练得到的识别模型提出了一种利用识别率进行紧固状态异常监测的方法。

【结果】

文章所提方法能够有效地监测动态缆紧固点的状态变化，并在发现异常情况时及时反应，从而保障了浮式风机的安全稳定运行。

【结论】

文章所提方法可用于动态缆扰动状态的分析和紧固点状态的在线监测，为深远海浮式风机的运维提供重要的数据支持。通过此方法，运维人员可以及时发现并处理紧固点的故障，保障浮式风机的稳定性和安全性。这为深远海浮式风机的运维提供了重要的技术支持，具有一定的实用价值和推广意义。

Abstract

【Objective】

The dynamic cable of the floating wind turbine in the deep sea enters the sea from the sea surface until it is buried on the seabed. The reliability of the dynamic cable is very important for the safe and stable operation of the floating wind turbine. The purpose of this study is to propose an effective solution to the monitoring problem of dynamic cable fastening points

and to verify its effectiveness in practical applications.

【Methods】

In order to achieve this goal

this paper first uses distributed optical fiber temperature measurement and acoustic wave detection technology to obtain temperature and disturbance information along the dynamic cable. These data provide the basis for subsequent analysis and processing. The spatial positioning of monitoring points is realized by using the temperature characteristics along the line. The key monitoring positions are determined as the bending point

buoy point and anchor chain point on the floating fan. Through the analysis and identification of the frequency domain characteristics of these monitoring points

the results show that the mutual recognition rate between the three monitoring points reaches 91%. Finally

based on the trained recognition model

a method for monitoring the abnormal state of fastening by using the recognition rate is proposed.

【Results】

This method can effectively monitor the state change of the dynamic cable fastening point and respond in time when abnormal conditions are found

thus ensuring the safe and stable operation of the floating fan.

【Conclusion】

The method proposed can be used for the analysis of dynamic cable disturbance state and on-line monitoring of fastening point state

which provides important data support for the operation and maintenance of floating wind turbines in deep sea. By using this method

the operation and maintenance personnel can find and deal with the fault of the fastening point in time to ensure the stability and safety of the floating fan. This provides important technical support for the operation and maintenance of deep-sea floating wind turbines

and has certain practical value and promotion significance.

关键词

Keywords

references

侯帅 , 王毅松 , 朱闻博 , 等 . 高压海底电缆监测技术与应用综述 [J ] . 南方电网技术 , 2023 , 17 ( 5 ): 49 - 58 .

Hou S , Wang Y S , Zhu W B , et al . Review of High Voltage Submarine Cable Monitoring Technology and Applications [J ] . Southern Power System Technology , 2023 , 17 ( 5 ): 49 - 58 .

蔡海文 , 叶青 , 王照勇 , 等 . 分布式光纤声波传感技术研究进展 [J ] . 应用科学学报 , 2018 , 36 ( 1 ): 41 - 58 .

Cai H W , Ye Q , Wang Z Y , et al . Progress in Research of Distributed Fiber Acoustic Sensing Techniques [J ] . Journal of Applied Sciences , 2018 , 36 ( 1 ): 41 - 58 .

高擎昊 , 苏幸晨 , 张成龙 , 等 . 基于偏振降噪的分布式光纤振动定位算法研究 [J ] . 仪表技术与传感器 , 2022 ( 12 ): 108 - 112 .

Gao Q H , Su X C , Zhang C L , et al . Research on Location Algorithm in Distributed Optical Fiber Vibration based on Polarization Noise Reduction [J ] . Instrument Technique and Sensor , 2022 ( 12 ): 108 - 112 .

汪洋 , 李捍平 , 林晓波 , 等 . 基于分布式光纤振动传感的海底电缆绝缘击穿故障检测 [J ] . 电线电缆 , 2018 ( 1 ): 31 - 34 .

Wang Y , Li H P , Lin X B , et al . Detection of Submarine Power Cable Insulation Breakdown based on Distributed Optical Fiber Vibration Sensor [J ] . Wire & Cable , 2018 ( 1 ): 31 - 34 .

Lindsey N J , Dawe T C , Ajo-Franklin J B . Illuminating Seafloor Faults and Ocean Dynamics with Dark Fiber Distributed Acoustic Sensing [J ] . Science , 2019 , 366 ( 6469 ): 1103 - 1107 .

徐承军 , 于佰宁 , 秦懿 . 基于深度域适应迁移学习的滚动轴承故障诊断方法研究 [J ] . 起重运输机械 , 2024 ( 7 ): 65 - 72 .

Xu C J , Yu B N , Qin Y . Research on Fault Diagnosis Method of Rolling Bearing based on Adaptive Migration Learning in Depth Domain [J ] . Hoisting and Conveying Machinery , 2024 ( 7 ): 65 - 72 .

韩颖 , 张旭 , 于明鑫 , 等 . 基于改进LSTM的FBG传感网络光谱基线校正方法 [J ] . 光通信研究 , 2024 ( 4 ): 230032 .

Han Y , Zhang X , Yu M X , et al . Baseline Correction Method of FBG Sensor Network Spectrum based on the Improved LSTM Model [J ] . Study on Optical Communications , 2024 ( 4 ): 230032 .

Yu Y , Si X , Hu C , et al . A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures [J ] . Neural Computation , 2019 , 31 ( 7 ): 1235 - 1270 .

邢炜光 , 赵赞善 , 邢锰 , 等 . 光纤传感用于海缆扰动探测的试验研究 [J ] . 光学精密工程 , 2023 , 31 ( 10 ): 1432 - 1442 .

Xing W G , Zhao Z S , Xing M , et al . Experimental Research on Submarine Cable Disturbance Detection with Optical Fiber Sensing [J ] . Optics and Precision Engineering , 2023 , 31 ( 10 ): 1432 - 1442 .

耿坤 , 吕枫 . 基于PCA/LSTM的海底观测网电力系统供电海缆故障定位 [J ] . 海洋技术学报 , 2020 , 39 ( 3 ): 22 - 29 .

Geng K , Lü F . PCA/LSTM-based Submarine Cable Fault Location Approach for Seafloor Observatory Network Power Systems [J ] . Journal of Ocean Technology , 2020 , 39 ( 3 ): 22 - 29 .

Lu J , Feng W , Li Y , et al . VMD and Self-Attention Mechanism-based Bi-LSTM Model for Fault Detection of Optical Fiber Composite submarine Cables [J ] . EURASIP Journal on Advances in Signal Processing , 2023 ( 1 ): 29 .

Chen Y , Li X , Zhao S . A Novel Photovoltaic Power Prediction Method based on a Long Short-Term Memory Network Optimized by an Improved Sparrow Search Algorithm [J ] . Electronics , 2024 , 13 ( 5 ): 993 .

茆习文 , 王海涛 , 张更新 . 卫星物联网负载量估计及预测 [J ] . 光通信研究 , 2024 ( 5 ): 230013 .

Mao X W , Wang H T , Zhang G X . Satellite Internet of Things Load Estimation and Prediction [J ] . Study on Optical Communications , 2024 ( 5 ): 230013 .

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