ABSTRACT
Slope failure cause lots of casualties and assets loss. An early-warning system based on the fiber optic sensors and stability analysis with the Bayesian updating is proposed in this study. Fiber optic sensors has high accuracy and long-term stability, thus it could be employed for long-term measurement in slopes. In this study, a GFRP reinforced slope was used as an example to employ the slope health monitoring approach. The distributed BOTDA optical fiber sensors were successfully applied in quality evaluation and performance monitoring of an excavated slope. The random field modeling was incorporated in the model updating analysis to reduce the uncertainty of the soil parameters (e.g. cohesion c and friction angle φ). With the updating model, the slope stability could be verified with the field measurement data and further employed for stability evaluations, thus it could provide more accurate results for the health condition of the instrumented slope. This study could provide references for the slope stability evaluation system with smart sensing and on-line preformation evaluation.
