Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems

This dataset was collected using a Distributed Acoustic Sensing (DAS) system with phase-sensitive Optical Time-Domain Reflectometry (Φ-OTDR) technology. It includes labeled and unlabeled acoustic signal measurements gathered around a university campus, covering activities such as walking, running, vehicular movement, and potential security threats like fiber manipulation and fence climbing. The data was captured using an Optasense ODH-F DAS interrogator, which monitors signals from a buried single-mode fiber optic cable. The dataset, stored in HDF5 format, serves as a critical resource for training machine learning models aimed at event classification in DAS systems. Each event is identified by power spectral density (PSD) representations and labeled accordingly. This dataset is ideal for researchers developing and validating machine learning algorithms for DAS-based applications, including structural health monitoring and perimeter security.

搜集汇总

背景与挑战

背景概述

该数据集是一个用于分布式声学传感（DAS）系统事件分类的综合性资源，采用相位敏感光时域反射（Φ-OTDR）技术，采集了大学校园周围包括行走、跑步、车辆移动和安全威胁等多种活动的声学信号数据。数据以HDF5格式存储，提供功率谱密度表示和相应标签，适用于训练和验证机器学习模型，支持结构健康监测和周边安全等应用。