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采煤塌陷区土地动态沉降预测模型
引用本文:张子月,邹友峰,陈俊杰,王云广.采煤塌陷区土地动态沉降预测模型[J].农业工程学报,2016,32(21):246-251.
作者姓名:张子月  邹友峰  陈俊杰  王云广
作者单位:1. 河南理工大学测绘与国土信息工程学院,焦作,454003;2. 河南理工大学能源科学与工程学院,焦作,454003
基金项目:国家自然科学基金联合基金项目(U1261206)
摘    要:为了把握采煤塌陷区土地复垦的时机、促进农业生产的持续高效,对塌陷区土地随时间不断变化的动态沉降过程进行了研究。通过分析Knothe函数中时间影响参数c,得出c值对地表沉降的动态计算及稳定时间有较大影响,且参数c是动态变化的,给出了c值的计算方法。依据塌陷区极限下沉量和阶段下沉量的思想,建立了基于时间影响参数的塌陷区动态沉降预测模型,并以某矿2407工作面的地表沉陷实测数据为例,对参数c的求取和预测模型进行了实例应用,结果表明该动态沉降预测模型较为符合现场实际。

关 键 词:煤矿  土地复垦  模型  塌陷区  动态沉降  时间影响参数  农业生产
收稿时间:2016/4/14 0:00:00
修稿时间:2016/8/26 0:00:00

Prediction model of land dynamic settlement in coal mining subsidence area
Zhang Ziyue,Zou Youfeng,Chen Junjie and Wang Yunguang.Prediction model of land dynamic settlement in coal mining subsidence area[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(21):246-251.
Authors:Zhang Ziyue  Zou Youfeng  Chen Junjie and Wang Yunguang
Institution:1. College of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China,1. College of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China,1. College of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China and 2. College of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China
Abstract:Abstract: The surface of the coal mining subsidence area will continue to sink at a relatively slow speed until it reaches limit, and the continuous settlement will inevitably affect the choice of land reclamation time, the growing crops which need nutrients from the land, and the normal use of agricultural facilities. It is very necessary to study the dynamic settlement of land over time to guarantee the time of land reclamation and the effectiveness of agricultural production. Time effect parameter in the Knothe function was analyzed in this study, and found that the parameter value had a great influence on the dynamic calculation of the surface subsidence and stability time. In the short period after mining, the bigger the parameter was, the greater the surface subsidence, and vice versa. And the bigger the parameter, the shorter the time needed for the surface from starting sinking to reaching the stability, and vice versa. In fact, the parameter was changing over time; the parameter in different periods were obtained based on the surface dynamic subsidence and time firstly, then the values were fitted, and the parameter in any period could be obtained according to the fitted formula. The dynamic settlement of coal mining subsidence area was closely related to the time; the Knothe function was introduced into the probability integral model, and the new idea of the ultimate subsidence and stage subsidence in the coal mining subsidence area was proposed. The prediction model of land dynamic settlement in coal mining subsidence area was constructed based on the Knothe function, which could be used to calculate the stage subsidence value at any time according to the engineering requirements. The subsidence factor, which changed with the time and was obtained from the time effect parameter, was the most important parameter in the prediction model. In order to verify the reliability and practicability of the prediction model, the paper took the measured surface subsidence data from the 2407 working face as an example, and carried out the application of the model as well as got the parameter. The time effect parameter at the 6th, 7th, 8th, 9th and 10th observation were calculated, respectively, and the empirical formula of the time effect factor with the time was obtained by fitting. By using the fitting formula, the time effect factor at the 11th observation was calculated. The calculated and the actual observation value of the time effect factor were compared, and the relative error was only 2.6% and the fitting effect was good. In addition, the measured and predicted values of the surface subsidence at the 9th observation were compared and analyzed. The results showed that the maximum relative error of single point was 8.8%, the average relative error of single point was 1.2%, the overall root mean square error was 187 mm, and the overall relative root mean square error was 5.6%. The difference between the predicted and measured value was small, which further proved the reliability of the model. According to the calculation model, the ultimate and the stage subsidence in multiple periods for the surface of coal mining subsidence area were calculated. The analysis showed that the prediction model conformed to the actual condition.
Keywords:coal mines  land reclamation  models  subsidence area  dynamic settlement  time effect parameter  agricultural production
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