LI D Y, WANG Z G, WANG S, et al. Research on the intelligent coordinated top-coal caving model and key technologies in extra-thick coal seams[J]. Journal of Henan Polytechnic University(Natural Science) , 2025, 44(3): 22-33.

doi:10.16186/j.cnki.1673-9787.2024060059

Received:2024/06/28

Revised:2025/03/17

Online:2025-04-18

Research on the intelligent coordinated top-coal caving model and key technologies in extra-thick coal seams

LI Dongyin1,2, WANG Zuguang1, WANG Shen1,2,3, LI Huamin1, PENG Weiping4, LI Hongbin1,2, ZHANG Guopeng5, ZHANG Xuhe6

1.School of Energy Science and Engineering， Henan Polytechnic University， Jiaozuo  454000， Henan， China；2.Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization， Jiaozuo  454000， Henan， China；3.Postdoctoral Station of Geological Resources and Geological Engineering， Henan Polytechnic University， Jiaozuo  454000， Henan， China；4.Information Construction and Management Center， Henan Polytechnic University， Jiaozuo  454000， Henan， China；5.School of Electrical Engineering and Automation， Henan Polytechnic University， Jiaozuo  454000， Henan， China；6.Zhengzhou Coal Mining Machinery Group Co.， Ltd.， Zhengzhou  450000， Henan， China

Abstract: Objectives Fully mechanized top-coal caving is a safe and efficient mining method for extra-thick coal seams. However， the complexity of the caving environment， the challenges in coordinating mining and caving， and the numerous factors influencing caving parameters have hindered the development of intelligent fully mechanized top-coal caving， particularly in terms of automated coal caving control technology. Methods To address the challenges of intelligent coal caving control under group caving conditions in fully mechanized top-coal caving faces of extra-thick coal seams， this study employs theoretical analysis， laboratory simulation experiments， computer control software development， and field trials. The research follows the framework of “mechanism of intelligent group caving-theory and methods of mining-caving coordination control-decision-making model for coal caving processes-field application of coal caving software.”  Results The study proposes a multi-outlet group cooperative caving method. Taking the continuous group caving method as an example， the spatial relationship between the top-coal caving body and the coal-rock interface under group cooperative caving is revealed. By analyzing the coordination relationship between mining and caving and the logic of group caving in fully mechanized top-coal caving faces， this study establishes a theoretical framework for intelligent mining-caving coordination control in extra-thick coal seams. A coordinated control model for mining and caving in terms of time， space， and material transport capacity is developed， along with a group caving decision-making method based on reinforcement learning and the Hidden Markov Random Field （HMRF） model， providing a reliable theoretical foundation for intelligent caving decision-making and precise control. Furthermore， a multi-source information database for fully mechanized top-coal caving faces is established by integrating geological information with mining and caving process parameters， laying the groundwork for intelligent decision-making and digital twin applications.  Conclusions Based on the mining-caving coordination characteristics under group caving conditions， an intelligent caving decision-making model is developed， and an intelligent caving decision support system （software） is independently designed and implemented. Field application of this software has enabled an annual coal production capacity of 15 million tons in intelligent fully mechanized top-coal caving faces.

Key words: extra-thick coal seam; fully mechanized top-coal caving; intelligent coal caving;mining-caving coordination; group caving