Optimization of distributed acoustic sensors based on fiber optic technologies

This research investigates distributed acoustic sensors (DAS) based on fiber optic technologies, focusing on the impact of pressure on signal-to-noise ratio (SNR), noise levels, and dominant frequency shifts. DAS systems are widely used for infrastructure monitoring due to their ability to capture acoustic signals over long distances, making them ideal for seismic and pipeline monitoring. The study examines how fluctuating pressure affects DAS performance, particularly signal quality and noise reduction. In applications like pipeline leak detection and seismic monitoring, pressure changes can degrade signal clarity and complicate anomaly detection. Understanding this relationship is key to optimizing DAS performance and improving system efficiency. The experiment varied pressure from 0.1 atm to 5 atm, showing that increased pressure raised SNR from 10 dB to 48 dB, reduced noise from 10 dB to 7 dB, and shifted the dominant frequency from 0.5 Hz to 3 Hz. Fourier analysis provided insights into these frequency spectrum changes. Higher pressure compresses the medium, enhancing signal isolation and improving SNR while reducing noise. The frequency shift results from changes in acoustic wave propagation speed under higher pressure, highlighting its role in signal processing. The key finding is that higher pressure significantly improves signal quality and reduces noise, enhancing DAS performance. The frequency shift improves environmental detection capabilities. These results are valuable for DAS applications in environments with pressure variations, like pipeline monitoring, where high signal quality is crucial. Improved signal fidelity and frequency shifts make DAS systems more reliable for long-term monitoring and contribute to accurate anomaly detection