分布式声学传感在海缆锚害监测中的应用（特邀）

张鸿; 吴明埝; 王道根; 穆章健; 谢书鸿; 吴正明; 李松林; 陈青青

doi:10.13756/j.gtxyj.2025.250098

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分布式声学传感在海缆锚害监测中的应用（特邀）

专题：海洋通信与传感网络 | 更新时间：2025-08-16

- 分布式声学传感在海缆锚害监测中的应用（特邀）
- Application of Distributed Acoustic Sensing in Anchor Damage Monitoring on Submarine Cables
- 光通信研究 2025年第4期
- 作者机构：
  
  1.中天电力光缆有限公司，江苏　南通　226463
  2.江苏中天科技股份有限公司，江苏　南通　226463
- 作者简介：
  
  张鸿，助理工程师。E-mail：flamse@163.com
- 基金信息：
  
  江苏省科技项目产业前瞻与关键核心技术资助项目(BE2022130)
- DOI：10.13756/j.gtxyj.2025.250098
  中图分类号： P716;TP212
- 收稿日期：2025-03-18，
  
  修回日期：2025-04-10，
  
  纸质出版日期：2025-08-10
- 稿件说明：
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张鸿，吴明埝，王道根，等. 分布式声学传感在海缆锚害监测中的应用[J]. 光通信研究，2025(4): 250098.

Zhang H, Wu M N, Wang D G, et al. Application of Distributed Acoustic Sensing in Anchor Damage Monitoring on Submarine Cables[J]. Study on Optical Communications, 2025(4): 250098.
张鸿，吴明埝，王道根，等. 分布式声学传感在海缆锚害监测中的应用[J]. 光通信研究，2025(4): 250098. DOI： 10.13756/j.gtxyj.2025.250098.

Zhang H, Wu M N, Wang D G, et al. Application of Distributed Acoustic Sensing in Anchor Damage Monitoring on Submarine Cables[J]. Study on Optical Communications, 2025(4): 250098. DOI： 10.13756/j.gtxyj.2025.250098.

摘要

【目的】

文章提供了一种使用光纤和分布式声学传感（DAS）技术来监测海缆锚害事件的算法，用于在缺乏数据的场景中基于特征阈值识别锚害事件，避免了高成本的锚害数据获取，同时增强了算法的广泛适用性。

【方法】

文章所提算法基于锚害事件的高强度、长距离和长时间作用特性，采用DAS测量海缆光纤得到的二维时空振动数据，基于平均功率特征掩模得到事件数据的轮廓，并计算轮廓面积和锚害置信度用于过滤轮廓，然后在等间隔时间段上计算轮廓形态学特征曲线，通过形态学特征曲线的强度和时间分布来识别锚害入侵事件。

【结果】

锚害模拟实验结果表明，文章所提算法计算出的形态学特征曲线在正常干扰和模拟锚害事件中差别明显，不同特征曲线的组合计算值可区分出事件轮廓的缺陷等特点，通过设定形态学特征阈值可快速识别出锚害事件。在模拟的1组锚害数据和两组非锚害数据中，算法通过对特征曲线强度和持续时间的过滤以及基于特征曲线的轮廓缺陷排查，成功识别出了锚害数据。

【结论】

文章所提海缆锚害监测算法在实现时主要采用OpenCV计算机视觉计算框架，计算速度快，准确率高，能满足海缆锚害监测的实时监测要求。形态学特征曲线在算法中能很好地表现出事件轮廓在时间上的分布情况，作为锚害算法的核心特征，扩展了形态学特征的应用场景，具有较高的应用价值。

Abstract

【Objective】

The article presents an algorithm utilizing optical fibers and Distributed Acoustic Sensing (DAS) technology for monitoring anchor-induced damage events in submarine cables. The algorithm enables feature-threshold-based identification of anchor hazards in data-scarce scenarios

circumventing the high costs associated with anchor damage data acquisition while enhancing the algorithm's broad applicability.

【Methods】

Based on the characteristic attributes of anchor damage events (high intensity

long-range impact

and prolonged duration)

the algorithm processes two-dimensional spatiotemporal vibration data obtained through DAS measurements of submarine cable fibers. It first extracts event data profiles using average power feature masking

then calculates contour area and anchor damage confidence to filter profiles. Subsequently

morphological feature curves are computed for profiles at equally spaced time intervals

enabling identification of anchor intrusion events through intensity and temporal distribution analysis of these curves.

【Results】

Simulation experiments demonstrate significant differences in morphological feature curves between normal interference and simulated anchor damage events. The combined computation of multiple feature curves effectively distinguishes profile defects in event contours. By setting morphological feature thresholds

anchor damage events can be rapidly identified. In the tests using one anchor damage dataset alongside two non-damage datasets

the algorithm effectively distinguished the anchor damage data by employing filtering techniques based on the intensity and duration of feature curves

as well as by detecting profile defects in these curves.

【Conclusion】

The submarine cable anchor damage monitoring algorithm proposed in this article primarily utilizes the OpenCV computer vision framework for its implementation. It features fast computation speed and high accuracy

meeting the real-time monitoring requirements for submarine cable anchor damage detection. The morphological feature curves used in the algorithm effectively represent the temporal distribution of event contours. As the core feature of the anchor damage algorithm

they expand the application scenarios of morphological features and hold significant practical value.

关键词

Keywords

references

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