Multi-scale monitoring and safety assessment of a prefabricated subway station integrating space-borne InSAR, ground-based machine vision and internal-distributed fiber optic sensors

Abstract

Safety monitoring of prefabricated subway stations is essential for early detection of potential damages to mitigate major accidents. This study developed an integrated multi-scale safety assessment and monitoring strategy for a prefabricated subway station by combining space-borne synthetic aperture radar interferometry (InSAR), ground-based machine vision, and internal-distributed fiber optic sensing (DFOS) technologies. Compared to the traditional single-data-source-monitoring method, the proposed space-ground-internal integration strategy is designed to monitor the multi-scale damages of prefabricated subaway stations. This includes the mm level of ground subsidence, submm level of structural surface deformation, and microstrain level of structural internal strain field. Taking the prefabricated Shapu Station in Shenzhen as the research site, the spatiotemporal evolution of land subsidence, the underground structural settlement and convergence deformation, as well as the structural internal strain changes were monitored. Then, a multi-scale data fusion methodology combining the space-borne InSAR, the ground-based machine vision, and the internal DFOS measurements was presented for effective safety assessment of the subway station. The monitoring results indicated that deformation occurred during the backfill period, and the settlement of the dangerous assembly ring increased (the seventh ring was at the lowest safety level) when the backfill of the assembly section was completed.

Keywords

• InSAR
• machine vision
• distributed fiber optic sensors
• safety assessment
• prefabricated subway station