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基于开采沉陷实测数据的Weibull时间函数模型参数研究

Study on parameters of Weibull time function model based on sited measuredmining subsidence data

  • 摘要: 常村煤矿井田范围内铁路专用线下压煤量达3 500万t,在煤炭资源开采的同时还要保障铁路的安全运营,因此开展开采动态沉陷预测尤为重要。为准确预计该井田采动地表移动变形的动态过程,实施合理的地表抗采动措施对工作面开采方案实施优化,引入Weibull时间函数,通过理论计算与软件处理相结合的方式,分析了该函数在下沉量、下沉速度、下沉加速度方面的变化特征。研究结果表明:计算结果与常村煤矿的实测地表下沉量一致,表明该函数在时间和空间上具有很好的完备性;在对常村煤矿地表动态沉陷监测数据进行整理分析的基础上,选取了11个监测点数据进行拟合处理和对比分析,研究确定了模型参数c、k的主要影响因素,同时给出了参数c、k的变化规律和变化曲线,并通过实测数据论证了其可靠性。最后,基于上述研究,选取22、30号监测点,通过对下沉实测值和预测值的动态对比分析,发现预计相对精度分别为2.11%和2.66%,表明Weibull时间函数模型及参数确定方法对改进采动地表动态沉陷过程预计是可靠的。

     

    Abstract: In Changcun Coal Mine, the coal deposit under the railway special line reaches 35 million tons. It is particularly important to ensure the safe operation of the railway while promoting the comprehensive development and utilization of coal resources. In order to accurately predict the dynamic process of mining surface movement and deformation,and provides the foundation for the measures of surface mining resistance and the optimization design of working face,based on Weibull time function model. Firstly, by combining theoretical calculation with software processing, the variation characteristics of the function in terms of subsidence amount, subsidence velocity and subsidence acceleration are analyzed. The results are consistent with the surface subsidence characteristics of Changcun Coal Mine, indicating that the function has good completeness in time and space. Then on the basis of collating and analyzing the monitoring data of surface dynamic subsidence in Changcun Coal Mine, selected the 11 monitoring data fitting processing and comparison analysis, the research determines the main influencing factor of the model parameters c and k, at the same time put forward the parameters c and k change rule and change curve, and through the measured data demonstrates the reliability. Finally, based on the above research, we select No. 22 and No. 30 monitoring point, and through dynamic comparison and analysis of measured and predicted values of subsidence, it is found that the predicted relative accuracy is 2.11% and 2.66%, respectively. Weibull time function model and parameter determination method have certain theoretical and practical significance for improving the prediction accuracy of mining surface dynamic subsidence process.

     

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