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边坡系统演化过程具有高度非线性特点,准确刻画系统演变内在规律对边坡稳定分析和预警至关重要。借助时间序列分析手段,利用自相关函数法确定边坡位移监测时间序列最佳延迟时间;利用G-P法确定嵌入维数和关联维数,继而重构位移序列相空间;利用小数据量法计算位移时序最大Lyapunov指数(M_(MLE)),借助关联维数和M_(MLE)对边坡系统演化过程进行混沌特征判定,确定影响边坡稳定的主要因素,挖掘边坡系统演变机理,并借助表征量实现边坡系统稳定性和稳定度分析。将该实测位移序列进行分段处理,描绘并分析其关联维数和M_(MLE)变化规律,指出边坡系统的演化规律一直存在混沌特性,这为边坡预警提供了借鉴。
The evolution of the slope system is highly nonlinear. It is very important to accurately characterize the inherent law of system evolution for slope stability analysis and warning. Using the method of time series analysis, the optimal delay time of slope displacement monitoring time series is determined by using the autocorrelation function method. The embedding dimension and correlation dimension are determined by GP method, and the phase space of the displacement sequence is reconstructed. The displacement The largest Lyapunov exponent of time series (M_ (MLE)), chaos feature is used to judge the evolution of slope system by means of correlation dimension and M_ (MLE), the main factors affecting slope stability are determined, the evolution mechanism of slope system is tapped, Slope system stability and stability analysis. The measured displacement sequence is segmented, and the correlation dimension and M_ (MLE) variation rule are depicted and analyzed. It is pointed out that the evolution law of slope system always has chaos characteristics, which provides a reference for slope warning.