这个论文发布了北海海底光缆的DAS数据集，带7.4万条标注，可做船只检测和距离估计，防电缆被破坏。
该论文发布Marlinks-NS DAS数据集，包含74,771个标注实例，来自北海28公里埋地光缆中2,554米段连续10天的记录。数据集定义了船只检测和船只到电缆距离估计两个机器学习任务。每个实例包含250个传感通道的光谱能量特征，以及AIS衍生的距离和元数据。该数据集旨在支持可复现的海底电缆保护研究。
A Distributed Acoustic Sensing Dataset for Vessel Detection and Localization in Submarine Cable Protection
Recent incidents of accidental damage and suspected sabotage to submarine telecommunication and power cables, particularly in the Baltic Sea, have underscored their vulnerability and the need for continuous monitoring solutions. Distributed acoustic sensing (DAS) applied to submarine optical-fiber cables enables wide-area monitoring of underwater acoustic activity. We present the Marlinks-NS DAS dataset, comprising processed submarine DAS measurements and AIS-derived vessel information curated for cable-protection research. The dataset defines two machine-learning tasks (vessel detection and vessel-to-cable distance estimation) allowing reproducible research under realistic marine conditions. The dataset contains 74,771 labeled data instances from ten days of continuous recording along a 2,554 m segment in a 28 km buried fiber-optic cable in the North Sea. Each instance includes spectral-energy features from 250 sensing channels, together with anonymized distance measurements and metadata from AIS information. The released HDF5 data, documentation, processing description, and example code support reproducible development and evaluation of DAS-based vessel-monitoring methods for submarine cable protection.