基于混沌理论的掘进工作面煤与瓦斯突出特征研究

煤与瓦斯突出是一种极其复杂的动力现象,属于非线性动力系统在时空演化过程中的灾变行为。探索煤与瓦斯突出的规律性,对预防煤与瓦斯突出具有非常重要的理论和实践意义。为此,针对某掘进工作面的2组瓦斯涌出数据,应用非线性理论对其进行研究,探索煤与瓦斯突出预测的新方法。首先对经过预处理的时间序列进行相空间重构,分析了时间序列的混沌特征量,证明其混沌特性,并根据时间序列的混沌特征量提出了此时间序列的最大可预测时间。在此基础上,建立了基于混沌特征量的神经网络突出预测模型。

Study on Coal and Gas Outburst Characteristics in Heading Face Based on Chaos

Coal and gas outburst is a very complicated dynamic phenomenon,it can be regarded as a catastrophic behavior of non-linear dynamic system in the evolution process of time and space. The exploration of coal and gas outburst regularity has very important theoretical and practical significance for the prevention of coal and gas outburst. For this purpose,study was made on it according to two groups of gas emission data from some heading face and by using non-linear theory,and the exploration was conducted on new prediction method for coal and gas outburst. In the paper,the phase space reconstruction was first conducted for the preconditioned time series,the time-series' chaos characteristic quantity were analyzed and proved,the maximum predictable time series was put forward according to the time-series' chaos characteristic quantity. Finally,a neural network outburst prediction model was set up on the basis of chaos characteristic quantity.