基于时间分析法的煤矿瓦斯涌出量预测研究

Prediction of Coal Mine Gas Emission Based on Time Analysis Method

以提升煤矿开采工作安全性为目的,提出了基于时间分析法的煤矿瓦斯涌出量预测方法,提升煤矿瓦斯涌出量预测效果。首先采用灰色理论、傅里叶级数、自回归模型阶数分别建立煤矿瓦斯涌出量时间序列的趋势项预测模型、周期项预测模型和随机项预测模型,后对趋势项、周期项与随机项预测模型的结果进行加权融合,得到瓦斯涌出量预测结果,最后进行了仿真实验。结果表明:该方法准确描述煤矿瓦斯涌出量的趋势、周期与随机性变化特点,在不同煤层埋深与不同煤层倾角时,该瓦斯涌出量预测的精度均较高。

With the aim of improving the safety of coal mining work,a coal mine gas emission prediction method based on time analysis is proposed to improve the prediction effect of coal mine gas emission.First,the grey theory,Fourier series and the order of autoregressive model are respectively used to establish the trend item prediction model,periodic item prediction model and random item prediction model of the coal mine gas emission time series.Then,the results of the trend item,periodic item and random item prediction model are weighted and fused to obtain the gas emission prediction results.Finally,the simulation experiment is carried out.The results show that the method accurately describes the trend of coal mine gas emission,the characteristics of periodic and random changes indicate that the accuracy of gas emission prediction is relatively high at different coal seam burial depths and dip angles.