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瓦斯涌出受地质构造、瓦斯煤层厚度、煤层孔隙结构等诸多非线性因素的影响,其行为蕴含着混沌特性。应用混沌理论,分析了瓦斯涌出的混沌行为。针对传统CC方法的不足,提出了用于优化时间延迟和嵌入维参数选取的改进CC方法,改进的CC方法可在重构相空间中更好地展现瓦斯涌出的混沌特性,为瓦斯涌出预测提供了可靠的精度。通过对瓦斯实验数据的分析,改进CC方法获得了较高精度的相空间参数和预测结果,并且最大Lyapunov指数也说明了瓦斯混沌特性的存在。
Gas emission is affected by many non-linear factors, such as geological structure, gas seam thickness and coal seam pore structure, and its behavior contains chaos characteristics. Chaos theory is applied to analyze the chaos of gas emission. In order to overcome the shortcomings of traditional CC methods, an improved CC method is proposed to optimize the time delay and the selection of embedded dimension parameters. The improved CC method can better reveal the chaos characteristics of gas emission in reconstructed phase space, Prediction provides reliable accuracy. By analyzing the experimental data of gas and improving the CC method, the phase space parameters and prediction results with higher accuracy are obtained, and the maximum Lyapunov exponent also shows the existence of gas chaos characteristics.