Application of distributed fiber-optic sensing in mining pressure and overburden monitoring in three-dimensional similarity simulation experiments

The manifestation of mining pressure and overburden deformation in mining fields is one of the critical issues that cannot be avoided in the safe and efficient extraction of coal. Precise monitoring and early warning of these factors are essential for disaster prevention and control. This study, based on three-dimensional similarity simulation experiments, integrates PPP-BOTDA distributed fiber-optic sensing technology with a self-developed traction displacement device to construct an internal deformation monitoring system for the model. The paper proposes a method for identifying roof pressure and quantifying overburden failure height using the average variation of the Brillouin frequency shift measured by optical fibers. Experimental results show that changes in the vertical Brillouin frequency shift curve are related to the degree of deformation of the overburden layers in the mining field. The more intense the overburden movement, the larger the change in the Brillouin frequency shift curve. This method successfully identified 16 instances of pressure occurrences during the advancement of the working face, with the step change in the average variation of the Brillouin frequency shift curve closely matching the location of the pressure. The fiber-optic monitoring of overburden failure deformation height was found to be 7%–15% higher than the surface observation results from the model, reflecting the high sensitivity of distributed fiber-optic sensing technology to small internal deformations in rock layers. The research results validate the accuracy and advancement of distributed fiber-optic sensing technology in monitoring mining pressure and overburden deformation in three-dimensional similarity simulation experiments. It overcomes the limitations of traditional monitoring methods that cannot obtain continuous deformation data from within, providing more options and security for safe mining and intelligent early warning systems.