Dejdar Petr, Mokry Ondrej, Munster Petr, Horvath Tomas, Schimmel Jiri
Brno University of Technology, Faculty of Electrical Engineering and Communications, Dept. of Telecommunications, Technicka 12, 61600, Brno, Czech Republic.
Sci Data. 2025 May 13;12(1):783. doi: 10.1038/s41597-025-05119-0.
Distributed acoustic sensing (DAS) is an emerging technology with diverse applications in monitoring infrastructure, security systems, and environmental sensing. This study presents a dataset comprising acoustic vibration patterns recorded by a commercial DAS system, providing valuable insights into the acoustic sensitivity of optical fibers. The data are crucial for evaluating the performance of DAS systems, particularly in scenarios related to security and eavesdropping. The dataset offers the possibility to develop and test algorithms aimed at enhancing signal-to-noise ratio (SNR), detecting anomalies, and improving speech intelligibility. Additionally, this resource facilitates the validation of de-noising techniques through the calculation of the speech transmission index (STI). The experimental setup, measurement procedures, and the characteristics of the DAS system employed are comprehensively documented for researchers in the field of optical fiber sensing and signal processing.
分布式声学传感(DAS)是一种新兴技术,在基础设施监测、安全系统和环境传感等领域有多种应用。本研究展示了一个数据集,该数据集包含由商用DAS系统记录的声学振动模式,为了解光纤的声学灵敏度提供了有价值的见解。这些数据对于评估DAS系统的性能至关重要,特别是在与安全和窃听相关的场景中。该数据集为开发和测试旨在提高信噪比(SNR)、检测异常以及改善语音清晰度的算法提供了可能性。此外,该资源通过计算语音传输指数(STI)促进了去噪技术的验证。针对光纤传感和信号处理领域的研究人员,全面记录了所采用的DAS系统的实验装置、测量程序和特性。