This application belongs to the field of
landslide prediction technology, and relates to a method for predicting landslides at tunnel entrances using shallow seismic-stress joint inversion. This invention acquires first-arrival wave
travel time data of the slope using a high-frequency seismic source array, constructs a geological model including a rock
mass integrity
coefficient matrix, identifies rock
mass structural deterioration through
elastic wave velocity distribution, and identifies potential unstable structural weak areas in advance. Then, the rock
mass integrity
coefficient matrix is embedded as prior knowledge into the
stress field solution. By establishing the
coupling relationship between
seismic wave propagation and stress, the
stress field distribution of the slope is inverted, capturing early
stress redistribution signals caused by structural deterioration in deep rock masses, achieving
early detection of precursors to
mechanical instability. Furthermore, based on stress and strain data, the
strain energy density distribution of the potential slip surface is calculated. By judging whether the
strain energy density exceeds a threshold, whether it is continuous, and whether the
expansion rate exceeds the standard, the potential slip surface can be accurately identified before it is fully connected, avoiding the
lag caused by relying on displacement signals.