Prediction of the critical value of the top slab of the 5-seam coal bed in Banji Mine
Yue Xizhan1, Li Yingfu2, Zhao Jiangmei2, Wang Guopu1, Sun Maoru1
1. China Coal Xinji Energy Co., Ltd., Huainan 232001, China; 2. School of Mining Engineering, Anhui University of Science and Technology, Huainan 232001, China
Abstract: The aim of this study is to explore the predictive patterns of the roof caving critical value in the 5th coal seam of Banji Coal Mine, analyze the impact of various factors, and apply grey system theory in the prediction process. Through sensitivity analysis, we have identified the key factors influencing the roof caving critical value, ranked as follows: roadway width (hw) > immediate roof thickness (hz) > old roof thickness (hj) > anchor cable length (Gj) > 5th coal thickness (hm) > mining depth (H). Furthermore, linear and nonlinear fitting were performed to establish the functional relationships for the roof caving critical value. Based on the fitted curves, the critical values for shallow and deep roof caving were calculated as 46mm and 27mm, respectively, with a total critical value of 73mm. In addition, grey system theory was employed to predict the roof caving amount after 377 days, and a grey forecasting model was trained using the GM(1,1) model. The prediction results indicate that the total roof caving amount at the 2# measuring point is 65mm, which aligns with the expected values and roof caving patterns. In summary, this study, through sensitivity analysis, has clarified the primary controlling factors and proposed targeted measures to reduce roof caving. Furthermore, we applied the grey model for caving prediction, demonstrating its advantages and potential applications in this field. This provides a viable forecasting method for coal mine safety production.
岳喜占1,李迎富2,赵江梅2,王国普1,孙茂如1. 板集煤矿5煤层顶板离层临界值预测研究[J]. 煤炭与化工, 2024, 47(6): 1- 6,13..
Yue Xizhan1, Li Yingfu2, Zhao Jiangmei2, Wang Guopu1, Sun Maoru1. Prediction of the critical value of the top slab of the 5-seam coal bed in Banji Mine. CCI, 2024, 47(6): 1- 6,13..