Research on the establishment of a mining subsidence prediction model under thick loose layer and its parameter inversion method

Abstract

Most of the coal mining in China is underground, which will inevitably cause surface deformation and trigger a series of geological disasters. Therefore, it is essential to find a suitable method to forecast the ground sinking caused by underground mining. The most commonly used prediction model in China is the probability integral model (PIM). But when this model is used in the geological condition of mining under thick loose layers, the predicted edge of the sinking basin will converge faster than the actual measured sinking situation. A geometric model (GM) with a similar model shape as the PIM but with a larger boundary value was established in this paper to solve this problem. Then an improved cuckoo search algorithm (ICSA) was proposed in this paper to calculate the GM parameters. The stability and reliability of the ICSA were verified through a simulated working face. At last, the ICSA, in combination with the GM and the PIM, was used to fit 6 working faces with the geological mining condition of thick loose layers in the Huainan mining area. The results prove that GM can solve the above-mentioned PIM problem when it is used in geological mining conditions of thick loose layers. And it was obtained through comparative analysis that the GM and the PIM parameters can take the same value except for the main influence radius.