Prediction model and parameter analysis of surface 
movement duration in deep coal mining

ZHANG Liang-liang; CHENG Hua; YAO Zhi-shu; WANG Xiao-jian

doi:10.16285/j.rsm.2023.0287

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Prediction model and parameter analysis of surface movement duration in deep coal mining

更新时间：2026-06-25

- Prediction model and parameter analysis of surface movement duration in deep coal mining
- Vol. 45, Issue 2, Pages: 577-587(2024)
- 作者机构：
  
  1. 安徽理工大学土木建筑学院,安徽,淮南,232001
  2. 安徽大学资源与环境工程学院,安徽,合肥,230022
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2023.0287
  CLC： TD325
- Online First：07 February 2024，
  
  Published：2024
- 稿件说明：
移动端阅览
ZHANG Liang-liang, CHENG Hua, YAO Zhi-shu, et al. Prediction model and parameter analysis of surface movement duration in deep coal mining[J]. 2024, 45(2): 577-587.
DOI：

ZHANG Liang-liang, CHENG Hua, YAO Zhi-shu, et al. Prediction model and parameter analysis of surface movement duration in deep coal mining[J]. 2024, 45(2): 577-587. DOI： 10.16285/j.rsm.2023.0287.

摘要

基于改进Knothe时间模型，根据地表移动延续时间定义，建立能够综合考虑采高、平均采深、松散层厚度、基岩层厚度和开采速度等因素的深部开采地表移动延续时间理论预测模型，并根据概率积分法给出了模型参数确定方法。采用24个深部工作面开采地表移动延续时间监测数据对预测模型的合理性和精确性进行验证。结果表明：地表移动延续时间模型预测结果与24个工作面监测结果基本吻合，两者平均绝对误差仅38 d，均方根误差仅为47 d，平均绝对误差百分比仅为9%，远小于现有3种经验模型的预测误差，验证了地表移动延续时间预测模型的精确性；地表移动延续时间受采高、平均采深、松散层厚度、基岩层厚度和开采速度的影响，随采高的增加而非线性增加，随平均采深、松散层厚度、基岩层厚度的增加而线性增加，但随开采速度的增加而非线性减小。该研究可为深部开采地表移动变形稳定性评估和科学制定开采计划提供理论指导。

Abstract

This paper presents a theoretical prediction model for the surface movement duration in coal mining

which takes into account various factors such as coal seam mining height

average mining depth

loose layer thickness

bedrock layer thickness

and mining speed. The model is based on the improved Knothe time model and incorporates the definition of surface movement duration. Additionally

a method for determining the model parameters using the probability integration method is provided. To validate the rationality and accuracy of the prediction model

monitoring data from 24 deep working faces are utilized. The results demonstrate that the predicted surface movement duration aligns well with the monitoring results from the working faces. The mean absolute error is only 38 days

the root mean square error is only 47 days

and the mean absolute percentage error is only 9%. These values indicate a significantly lower prediction error compared to existing empirical models. The accuracy of the surface movement duration prediction model is confirmed. The study further reveals that the duration is influenced by coal seam mining height

average mining depth

loose layer thickness

bedrock layer thickness

and mining speed. Specifically

it increases nonlinearly with coal seam mining height

linearly with average mining depth

loose layer thickness

and bedrock layer thickness

but decreases nonlinearly with mining speed. This research provides theoretical guidance for evaluating the stability of surface movement and deformation in coal mining and formulating scientifically sound mining plans.

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