Study on Influencing Factors of Blockage Signals in Highway Tunnel Drainage Pipelines Using Distributed Acoustic Sensing Technology

To address the impact of environmental and equipment factors on signal identification in highway tunnel drainage pipeline blockage monitoring, this study aims to elucidate the influence patterns of pipeline flow rate, optical fiber deployment scheme, and fiber performance on blockage-induced acoustic signals. A full-scale concrete pipeline experimental platform was established. Data were acquired using a HIFI-DAS V2 sensing system. The time–frequency domain characteristics of acoustic signals under different flow rates (50 m3/h and 100 m3/h), fiber deployment schemes (inside the pipe, outside the pipe, and outside a soundproofing layer), and fiber materials (six typical types) were analyzed and compared. The degree of influence of each factor on signal amplitude and dominant frequency components was quantified. The experimental results indicate that: Compared to a flow rate of 50 m3/h, the amplitude characteristic value at the blockage channel exhibited a marked increase at 100 m3/h, accompanied by an increase in the number and amplitude of dominant frequency components. While the dominant frequency components of the acoustic signals were less stable across the three deployment schemes, the overall amplitude at the blockage channel was consistently higher than that at non-blockage channels. When the fiber was deployed farther from the fluid core (outside the soundproofing layer), the dominant frequencies essentially disappeared, with energy distributed in a broadband form. The peak amplitude and array energy of the sensitive vibration sensing fiber were 2 times and 3.6 times those of the worst-performing type, respectively. Furthermore, its physical properties are better suited to the tunnel environment, effectively enhancing signal acquisition stability and the signal-to-noise ratio. Comprehensive analysis demonstrates that deploying sensitive fibers inside the pipe is more conducive to the accurate identification of blockage events. Moreover, uniform dominant frequency components and threshold criteria are not recommended along the entire length of the drainage pipe. This research provides theoretical and experimental support for parameter optimization of DAS systems to achieve high-precision pipeline blockage monitoring in complex tunnel environments.