基于空间混沌理论的钻屑气体解吸指数煤与瓦斯突出危险性预测方法

Li Dingqi , Cheng Yuanping , Wang Lei , Wang Haifeng , Wang Liang , Zhou Hongxing
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引用次数: 20

摘要

基于地质动力学演化和空间混沌理论,提出了预测煤与瓦斯突出的岩屑气体解吸指数超前预测方法。利用石台矿II3112煤巷钻屑气体解吸指数的空间序列数据,对该预测方法进行了验证。实验结果表明,钻屑气体解吸指数的空间分布具有一定的混沌特征,表明空间混沌理论可以预测煤与瓦斯突出的危险性。我们还发现,为了保证预测的准确性和实际可操作性,需要选择适量的样本数据。在合理选择预测速度的情况下,相对预测误差较小。在我们的实验中,样本点的最佳个数为80,最佳预测速度为30。相应的超前预测速度基本满足工程应用的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction method for risks of coal and gas outbursts based on spatial chaos theory using gas desorption index of drill cuttings

Based on the evolution of geological dynamics and spatial chaos theory, we proposed the advanced prediction an advanced prediction method of a gas desorption index of drill cuttings to predict coal and gas outbursts. We investigated and verified the prediction method by a spatial series data of a gas desorption index of drill cuttings obtained from the II3112 coal roadway at the Shitai Mine. Our experimental results show that the spatial distribution of the gas desorption index of drill cuttings has some chaotic characteristics, which implies that the risk of coal and gas outbursts can be predicted by spatial chaos theory. We also found that a proper amount of sample data needs to be chosen in order to ensure the accuracy and practical maneuverability of prediction. The relative prediction error is small when the prediction pace is chosen carefully. In our experiments, it turned out that the optimum number of sample points is 80 and the optimum prediction pace 30. The corresponding advanced prediction pace basically meets the requirements of engineering applications.

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