ZHAO C S, CHEN J J, YAN W T,et al.Construction and implementation of a subsidence prediction model for inclined irregular working face mining[J].Journal of Henan Polytechnic University(Natural Science) ,2026,45(2):204-212.

doi:10.16186/j.cnki.1673-9787.2025070033

Received:2025/07/26

Revised:2025/10/29

Published:2026/01/28

Construction and implementation of a subsidence prediction model for inclined irregular working face mining

Zhao Chunsu1, Chen Junjie1, Yan Weitao1,2

1.School of Surveying and Land Information Engineering， Henan Polytechnic University， Jiaozuo  454003， Henan， China；2.Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization， Jiaozuo  454003， Henan， China

Abstract: Objectives The prediction accuracy of surface movement and deformation under complex mining conditions is to be improved， and the surface movement and deformation induced by inclined irregular working face mining is to be accurately predicted. Methods Based on a unit influence function that considers variations in mining depth， a calculation method for the mining depth of arbitrary units in inclined coal seams was proposed， and a subsidence prediction model suitable for inclined irregular working faces was established. The model applies Green’s theorem to convert subsidence area integrals into boundary line integrals， derives the corresponding line integral prediction formula， and provides a numerical solution method. On this basis， an integrated prediction program was developed, achieving full-process computation from parameter input and determination of integration intervals to line integral solutions. The program enables visualization of prediction results， including surface subsidence， tilt， curvature， horizontal movement， and horizontal deformation, and further evaluates and analyzes the mining-induced damage levels. The proposed model was validated and analyzed through case studies of inclined working faces in actual mining areas.  Results The results show that the proposed prediction model and integrated program can effectively address the accurate prediction of surface subsidence and classification of mining-induced damage under complex mining conditions. The prediction results conform to the fundamental laws of mining subsidence， with a relative error in subsidence prediction of less than 10%， thereby meeting engineering accuracy requirements. Conclusions The proposed model is reliable and practical， with high prediction accuracy， and can provide a theoretical basis and technical support for the mining design optimization， precise surface damage assessment and protection strategies in inclined irregular working face mining.

Key words: mining subsidence prediction; irregular working face; inclined coal seam; probability integration method; Green’s formula