Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure.

Area of Science:

• Optical Fiber Sensing
• Signal Processing
• Acoustic Monitoring

Background:

• Distributed Acoustic Sensing (DAS) is an emerging technology with broad applications in infrastructure monitoring, security, and environmental sensing.
• Optical fibers possess inherent acoustic sensitivity, making them suitable for vibration detection.
• Existing datasets for DAS are limited, hindering the development of advanced signal processing techniques.

Purpose of the Study:

• To present a comprehensive dataset of acoustic vibration patterns recorded by a commercial DAS system.
• To provide valuable insights into the acoustic sensitivity of optical fibers for DAS applications.
• To facilitate the development and validation of algorithms for signal enhancement and anomaly detection in DAS.

Main Methods:

• Acquisition of acoustic vibration data using a commercial Distributed Acoustic Sensing (DAS) system.
• Detailed documentation of the experimental setup, measurement procedures, and DAS system characteristics.
• Inclusion of data suitable for evaluating signal-to-noise ratio (SNR) and speech transmission index (STI).

Main Results:

• A novel dataset of acoustic vibration patterns from DAS is made available.
• The dataset offers insights into the acoustic sensitivity of optical fibers.
• The data supports the evaluation of de-noising techniques and speech intelligibility.

Conclusions:

• The presented dataset is a valuable resource for researchers in optical fiber sensing and signal processing.
• It enables the development and testing of algorithms for improving DAS system performance in security and monitoring.
• The data facilitates validation of de-noising methods and acoustic analysis using the Speech Transmission Index (STI).