Multi-source aliasing suppression for distributed fiber acoustic sensing with directionally coherent enhancement technology
Zhaoyong Wang, Junqi Yang, Junzhe Gu, Bin Lu, Lei Ye, Ying Kang, Qing Ye, Ronghui Qu, Haiwen Cai
Abstract
Distributed fiber acoustic sensing (DAS) can detect almost all disturbances along the sensing fiber and is widely applied. However, the signals from multiple adjacent disturbance sources are superimposed, according to the sensing principle. A directionally coherent enhancement technology is demonstrated for DAS to suppress multi-source aliasing in air. In preliminary works, two situations are considered for feasibility verification. The submerged weak target signal is effectively extracted from strong broadband noise, and two different same-frequency signals from two sources are separately rebuilt with the same detected signal. As far as we know, this is the first time that the directionally coherent enhancement is proposed for DAS and the multi-source aliasing is suppressed. This technique will help DAS find new important foreground in acoustic detection of large-scale plants with many similar noisy devices, including discharge detection in high voltage substations and acoustic emission flaw detection in mechanical factories.