ISSN 2096-4498

   CN 44-1745/U

二维码

Tunnel Construction ›› 2026, Vol. 46 ›› Issue (S1): 375-386.DOI: 10.3973/j.issn.2096-4498.2026.S1.032

Previous Articles     Next Articles

Distributed Acoustic Sensing-Based Detection of Urban Hidden Karst

ZHANG Dan1, 2, CHENG Fei3, 4, XU Zhuoqun1, ZHANG Xiang3, 4, AI Zhiwei1, LIN Kai1   

  1. (1. Jiangsu Provincial Key Laboratory of Intelligent Sensing and Control of Integrated Traffic, Nanjing 210014, Jiangsu, China; 2. School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, Jiangsu, China; 3. Jiangsu Railway Group Co., Ltd., Nanjing 210012, Jiangsu, China; 4. Jiangsu Provincial Engineering Research Center of Intelligent and Green Railway, Nanjing 210012, Jiangsu, China)
  • Online:2026-06-30 Published:2026-06-30

Abstract: To fulfill the requirements of trenchless excavation, rapid deployment, and high-resolution imaging of urban hidden karsts, the influence of various cable-ground coupling mechanisms on distributed acoustic sensing (DAS) signals is examined and an optimized ambient noise imaging scheme is proposed. Initially, five coupling methods including soil burial, gypsum fixation, glue bonding, tape attachment, and sandbag coverage are evaluated by analyzing the signal-to-noise ratio and dispersion characteristics of active-source signals. Balancing construction efficiency with signal fidelity in urban road environments, the gypsum-fixation method is identified as the optimal deployment strategy. Subsequently, a field validation is conducted in the Shangyuanmen area in Nanjing, China. Using a metal-armored sensing cable as a linear array, continuous ambient noise data are recorded over several days. Surface-wave dispersion spectra are generated via the frequency-Bessel transform for an 80 m array, and fundamental-mode dispersion curves are extracted within the 5-40 Hz range. The shear-wave velocity structure of the upper 40 m is then reconstructed using a competitive particle swarm optimization algorithm. The results indicate that: (1) The DAS-based ambient noise imaging method produces shallow velocity profiles that accurately characterize the near-surface stratigraphy, showing high correlation with local borehole logs. (2) Distinct low-velocity anomalies are detected at distances of 70-120 m along the array. Integrated analysis with borehole cores—which reveal significant dissolution features—confirms that these anomalies correspond to active karst development zones.

Key words: fiber optic sensing, distributed acoustic sensing, karst, ambient noise tomography, shear wave