基于卡尔曼滤波法的工作面瓦斯涌出量预测研究

Study on Gas Emission Quantity Forecasting Based on Kalman Filter

针对矿井回采工作面瓦斯涌出量的非线性、时变性、复杂性和不确定性等特点,提出了卡尔曼滤波算法用于预测非线性动态瓦斯涌出量。通过建立数学模型并结合平煤13矿数据资料得出预测结果。结果表明:卡尔曼滤波法预测的平均误差为3.35%,比其它预测方法具有较高的精准度,该方法对回采工作面瓦斯涌出量的预测具有较好的跟踪能力和反应速度。

In the view of the mine working face gas emission of nonlinear, time - varying, complexity and uncertainty characteristics of kalman filtering algorithm was presented for predicting nonlinear dynamic gas emission. It has obtained predictions by establishing the mathematical model and combining the date of Thirteenth Coalmine of Pingdingshan Coal Group. The results show that the kalman filte- ring method to predict the average error is 3.35%, its＇precision is higher than other prediction methods, the method of working face gas emission prediction has a good tracking ability and speed of response.