This invention discloses a method for monitoring the relative gravity of surface
subsidence during
coal mining. It involves deploying
quantum gravity reference stations around the
subsidence area, arranging relative gravimeters in a
grid pattern within the basin, and arranging
fiber optic gravity sensor chains in the underground roadway. Simultaneously, a UAV equipped with a cold atom gravity
gradiometer performs periodic scans. Based on real-
time data, a gravity field-
mass migration model is established, correlating
coal extraction volume, changes in
rock density, and surface gravity anomalies.
Wavelet multi-scale
decomposition is used to eliminate geological background interference, and hydrological correction is applied, incorporating
water level and
porosity to optimize gravity variation values. When the corrected gravity variation exceeds a threshold, the
azimuth of rock fracture is calculated using the
gravity gradient tensor. Equivalent extraction thickness is derived based on gravity variation inversion, and the surface
subsidence morphology is dynamically predicted using a subsidence basin model. A
state vector is constructed by combining gravity, gradient, and deformation data, and multi-source fusion prediction is achieved through a filtering
algorithm.