Multi-Modal Weak Signal Analysis for Buried Optical Cable DVS Using Combined Multi-Head Attention Mechanism

Distributed optical fiber sensing technologies, particularly Φ-OTDR, have been extensively applied in vibration monitoring of critical infrastructure, including highways and pipelines. This is attributed to their capabilities of long-distance monitoring, high spatiotemporal coverage, and ease of deployment. Nevertheless, the monitoring data encompasses a mixture of information such as cable structural coupling, initial vibration states, and multi-modal environmental excitations. Consequently, effective separation and extraction of these signals are crucial for practical implementations. Notably, multi-modal weak signal analysis has emerged as a significant technical challenge in this field. Building upon the Φ-OTDR DVS fiber-environment coupled vibration observation model, this research introduces an innovative scenario-oriented analytical framework that integrates a combined multi-head attention mechanism. This advancement enables precise extraction of multi-modal weak signals within complex environments. Empirical validation utilizing measured data from a 30 km optical cable installed along an urban ring road has confirmed the framework’s exceptional performance across various scenarios. These include road surface roughness detection, construction machinery detection and localization, and vehicle trajectory recognition. The study reveals that the attention mechanism effectively concentrates on scenario-relevant signals, thereby substantially enhancing the analytical real-time performance. Overall, the proposed framework offers a versatile and real-time solution for DVS signal processing in intricate scenarios.