张兵, 崔希民, 赵玉玲, 李春意. 优化分段Knothe时间函数求参方法[J]. 煤炭学报, 2018, (12). DOI: 10.13225/j.cnki.jccs.2018.0369
引用本文: 张兵, 崔希民, 赵玉玲, 李春意. 优化分段Knothe时间函数求参方法[J]. 煤炭学报, 2018, (12). DOI: 10.13225/j.cnki.jccs.2018.0369
ZHANG Bing, CUI Ximin, ZHAO Yuling, LI Chunyi. Parameter calculation method for optimized segmented Knothe time function[J]. Journal of China Coal Society, 2018, (12). DOI: 10.13225/j.cnki.jccs.2018.0369
Citation: ZHANG Bing, CUI Ximin, ZHAO Yuling, LI Chunyi. Parameter calculation method for optimized segmented Knothe time function[J]. Journal of China Coal Society, 2018, (12). DOI: 10.13225/j.cnki.jccs.2018.0369

优化分段Knothe时间函数求参方法

Parameter calculation method for optimized segmented Knothe time function

  • 摘要: 针对优化分段Knothe时间函数的参数求取问题,给出了2种求参方法:(1)以本矿区,或地质、采矿条件相似矿区的地表监测资料为基础,提出了“反算时间函数对比求参法”,给出了详细的参数求取流程,该法直观、易操作,且具有通用性,可用于其他时间函数的参数求取;(2)以采空区达到充分采动尺寸时的地表沉陷规律,及相应概率积分参数为基础,推导了时间参数的“直接计算法”公式,该方法参数意义明确,求参过程简便,能直接应用于编程计算。预计实践表明,采用本文方法求参,动态预测最大相对误差可控制在9%以内,随着开采时间的增加,动态预测精度将会逐渐提高,最终维持在5%左右;根据统计,地表最大下沉值预测相对误差则可维持在6%左右。应用实践证明了论文所给出的求参方法的实用性与可靠性。

     

    Abstract: To overcome the problem of parameters calculation for optimal segmented Knothe time function,two calcula- tion methods are presented. Firstly,based on the surface monitoring data of a mining area,or mining areas with similar geological and mining conditions,the back-calculation and comparison method of parameter determination is proposed. It gives a detailed parameter calculation process,which is intuitive,easy to operate,and versatile,and can also be used to obtain the parameters for other time functions. Secondly,based on the surface subsidence law when the goaf reaches its full mining size,and the corresponding probability integration parameters,a “direct calculation method” of parame- ter determination is proposed. The parameters of the method are clear in meaning,and the process of parameter calcu- lation is convenient and can be directly applied to program calculation. Through the dynamic prediction practice,it is shown that the maximum relative error of the dynamic prediction can be controlled within 9% using the method de- scribed in the paper. With the increase of mining time,the dynamic prediction accuracy will gradually increase and it will eventually be maintained at around 5% . According to the statistics,the relative prediction error of the maximum surface subsidence can be maintained at around 6% . Application practice proves the practicability and reliability of the method proposed in the paper.

     

/

返回文章
返回