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李远耀, 殷坤龙, 程温明. R/S分析在滑坡变形趋势预测中的应用[J]. 岩土工程学报, 2010, 32(8).
引用本文: 李远耀, 殷坤龙, 程温明. R/S分析在滑坡变形趋势预测中的应用[J]. 岩土工程学报, 2010, 32(8).
Application of R/S method in forecast of landslide deformation trend[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(8).
Citation: Application of R/S method in forecast of landslide deformation trend[J]. Chinese Journal of Geotechnical Engineering, 2010, 32(8).

R/S分析在滑坡变形趋势预测中的应用

Application of R/S method in forecast of landslide deformation trend

  • 摘要: R/S分析(重标度极差分析)是一种描述和刻画非线性时间序列的有效方法。针对滑坡地表位移监测时序确定性与随机性共存的复杂非线性特征,对三峡库区的一个实例滑坡的长时期位移时序进行了R/S分析。分别计算了滑坡累积位移时序和增量位移时序的Hurst指数,指出增量位移时序是更有效的分形结构,其Hurst指数能定量刻画滑坡的变形趋势;分析了滑坡增量位移时序的非周期循环长度,发现滑坡前缘与中后部的增量位移时序Hurst指数和非周期循环长度存在显著差别,并从滑坡变形诱发机制上解释了这一差异产生的内在原因;最后基于滑坡变形演化的力学机理,提出了一个利用增量位移时序Hurst指数判断滑坡加速变形阶段的概念模型:为提高和完善滑坡失稳时间预测预报理论,提供了一个有意义的新思路和新方法。

     

    Abstract: The R/S analysis (rescaled range analysis) is one of efficient methods to characterize nonlinear time series. As the time series of monitoring surface displacement is not only deterministic but also random, the R/S analysis is used to analyze the long-term displacement time series of a landslide in the Three Gorges Reservoir area. The Hurst index of the accumulated displacement-time series and the incremental displacement-time series of the landslide are calculated by using the R/S analysis. The incremental displacement-time series is a more efficient fractal structure, and its Hurst index can depict quantitatively the deformation trend of the landslide. The concept of long range correlated critical time is introduced to analyze the non-periodic cycle length of the landslide displacement. The research indicates that the Hurst index and the non-periodic cycle length at different places of the landslide are different. Based on the physical mechanism of landslide deformation evolution, a conceptual model to determine the accelerating deformation phase according to the Hurst index of the incremental displacement-time series is proposed, and it provides a new method to improve the prediction of landslide failure time.

     

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