Ms. Semira Mohammed Ali Profile

Semira Mohammed Ali

at Scuola Superiore Sant'Anna

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Proceedings Article | 22 May 2023 Poster + Paper

An advanced signal processing scheme for real-time feature extraction in a distributed acoustic sensor based on phase demodulation with fast Hilbert transform

Semira Mohammed Ali, Fabrizio Di Pasquale, Yonas Muanenda

Proceedings Volume 12327, 123271Y (2023) https://doi.org/10.1117/12.2644956

KEYWORDS: Demodulation, Computation time, Signal processing, Feature extraction, Acoustics, Sensors, Phase modulation, Tunable filters, Modulation, Backscatter

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Phase-Sensitive Optical Time Domain Reflectometry (Φ-OTDR) is the most common implementation of a Distributed Acoustic Sensing (DAS) system and employs the observation of speckles resulting from Rayleigh Backscattering from coherent pulses in an optical fiber. Since they are sensitive to local disturbances altering the intensity and phase of light, perturbations induced by events cause changes in the speckle pattern whose precise measurement gives information on the amplitude and frequency of vibrations distributed along the fiber. Demodulation of the local phase change is key to the precise measurement of events since it is more linearly related to the strain applied to the fiber. One of the key issues in distributed sensing is that phase demodulation schemes usually require additional post-processing algorithm runs for each spatial location, which introduces delays, and hence reductions in dynamic sensing capability when scaled along the whole sensing distance. In this contribution, we analyze the impact of the post-processing in different phase demodulation techniques employing Phase-Generated Carrier (PGC) on the bandwidth of distributed feature extraction in a typical DAS system by quantifying the total computation time needed for a benchmark, 10-km sensing range at meter-scale spatial resolutions. We then design, implement, and analyze a signal processing scheme for phase extraction in Φ-OTDR enabling real-time dynamic measurements based on a Fast Hilbert Transform (FHT). Particular focus is given to the choice of this demodulation scheme for optimized bandwidth of distributed feature extraction using parallel processing of adjacent blocks in such a way that the overall throughput of spatially resolved concurrent demodulation allows dynamic vibration sensing at speeds relevant to most structural health monitoring applications.

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