Dynamic Monitoring of Goaf Stress Field and Rock Deformation Driven by Optical Diber Sensing Technology

Addressing the critical technological needs for the real-time monitoring of stress distribution in mining areas, a new method for inverting goaf pressure using distributed optical fiber monitoring data is proposed. By coupling the key stratum fracture mechanics model with the subsidence trajectory function model, a theoretical model is established to accurately describe spatial stress evolution during coal mining. The model quantifies the relationship between goaf pressure changes and key stratum failures through a two-stage analysis of the subsidence process, based on distinct mechanical properties before and after key stratum fracture. Physical model experiments (3 m × 0.2 m × 1.1 m) using Brillouin Optical Time Domain Analysis (BOTDA) technology validated the proposed method, with comprehensive monitoring of key stratum deformations. By coupling the fracture mechanics model of the critical layer and the settlement trajectory function model, the dynamic transformation of the pre-fracture and post-fracture stages is realized, and the stress evolution can be monitored and predicted in real time. The results demonstrate spatial consistency between key stratum fracture locations and goaf peak stress positions. High-precision optical fiber sensing detected an ultimate strain threshold of 4000 με for key stratum failure, with pre-fracture strain measurements consistently below this threshold. The developed stress inversion formula successfully predicted pressure distribution patterns within the goaf, achieving real-time monitoring capabilities. Compared with the BPPS measurements, the deviation in the inverted data is less than 8.88%, the root mean square error (RMSE) is 0.98–1.20 in different propulsion stages, and the coefficient of determination (R2) is between 0.72 and 0.85. These findings provide a crucial theory for predicting peak stress evolution in mining areas, with implications for improving safety monitoring systems and optimizing mining operations.