基于分形理论的隧道地表沉降分析及预测

左昌群,刘代国,丁少林,李林森

长江科学院院报 ›› 2016, Vol. 33 ›› Issue (4) : 51-56.

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长江科学院院报 ›› 2016, Vol. 33 ›› Issue (4) : 51-56. DOI: 10.11988/ckyyb.20150074
工程安全与灾害防治

基于分形理论的隧道地表沉降分析及预测

  • 左昌群,刘代国,丁少林,李林森
作者信息 +

Analysis and Prediction of Tunnel Surface SubsidenceBased on Fractal Theory

  • ZUO Chang-qun, LIU Dai-guo, DING Shao-lin, LI Lin-sen
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摘要

隧道地表沉降变形时间序列是具有分形特征的非线性体系,以狮子山隧道地表沉降监测为研究对象,基于分形理论,使用R/S分析法和V/S分析法计算了累计沉降和沉降速率时间序列的Hurst指数,并评价了地表沉降的稳定性,结合V统计量评价了这2种分析方法的有效性和地表变形的非循环周期;最后,使用分形插值函数与回归函数对地表沉降值进行了预测评价。结果表明,R/S分析法和V/S分析法对分析地表沉降时间序列具有较好的有效性,R/S分析法受短期记忆影响大,计算结果偏于安全,而 V/S分析法评价地表变形稳定性更加保守,3个监测点将长期处于稳定状态,且其时间序列的非循环周期约为20 d。使用分形插值得到的预测值与实测值间误差较小,且能正确反映变形演化趋势,较传统的回归分析优越,可以为地表沉降预测提供一种参考。

Abstract

The time series of tunnel surface deformation is a nonlinear system with fractal characteristics. According to the surface subsidence monitoring of lion rock tunnel, we calculated the Hurst index of time series of accumulated subsidence and subsidence rate by using the R/S and V/S analysis based on fractal theory. Moreover, we evaluated the stability of surface subsidence, and analyzed the effectiveness of R/S and V/S analysis methods and the non-cyclic period of surface deformation in association with V statistic. We also predicted the surface subsidence values by fractal interpolation function and regression function. Results show that both R/S and V/S analysis methods has good validity for the analysis of time series of surface subsidence. R/S analysis method is prone to be influenced by short-term memory, which makes the result safe; whereas V/S analysis method is more conservative. Three monitoring points will be in stable state for a long time, and the time series of non-cyclic period is about 20 days. Compared with measured value, the error of the predicted value obtained by fractal interpolation is small. The method in this paper could reflect the deformation evolution trend correctly, and is superior to traditional regression analysis.

关键词

地表沉降 / 变形时间序列 / 分形理论 / Hurst指数 / 分形插值

Key words

ground surface subsidence / deformation time series / fractal theory / Hurst index / fractal interpolation

引用本文

导出引用
左昌群,刘代国,丁少林,李林森. 基于分形理论的隧道地表沉降分析及预测[J]. 长江科学院院报. 2016, 33(4): 51-56 https://doi.org/10.11988/ckyyb.20150074
ZUO Chang-qun, LIU Dai-guo, DING Shao-lin, LI Lin-sen. Analysis and Prediction of Tunnel Surface SubsidenceBased on Fractal Theory[J]. Journal of Changjiang River Scientific Research Institute. 2016, 33(4): 51-56 https://doi.org/10.11988/ckyyb.20150074
中图分类号: TU94   

参考文献

[1]靳晓光,李晓红,高 茺,等.隧道围岩位移的灰色优化模型预测.重庆大学学报(自然科学版),2002,25(1):1-5.
乔志超,周建春. 隧道围岩变形监测及分析.施工技术,2012, (4):40-42.
HURST H E. Long-term Storage Capacity of Reservoirs: An Experimental Study. Transactions of American Society of Civil Engineers, 1951, 116: 770-808.
GIRAITIS L, KOKOSZKA P, LEIPUS R, et al.Rescaled Variance and Related Tests for Long Memory in Volatility and Levels. Journal of Econometrics, 2003, 112(2): 265-294.
MANDELBROT B B.The Fractal Geometry of Nature. San Francisco, USA: W. H. Freeman and Company, 1982.
DAVIDSON J, HASHIMZADE N. Type I and Type II Fractional Brownian Motions: A Reconsideration. Computational Statistics and Data Analysis, 2009, (53): 2089-2106.
李远耀,殷坤龙,程温鸣. R/S分析在滑坡变形趋势预测中的应用. 岩土工程学报,2010,(8):1291-1296.
贺可强,孙林娜,王思敬. 滑坡位移分形参数Hurst指数及其在堆积层滑坡预报中的应用. 岩石力学与工程学报,2009,(6):1107-1115.
陈学习,宋富美,闫智婕. 基于分形理论的瓦斯涌出规律. 辽宁工程技术大学学报(自然科学版),2012,(5):617-620.
乔美英,陈 鑫,兰建义. 基于V/S分析的瓦斯涌出量分形特性研究. 中国煤炭,2014,(10):104-110.
李业学,刘建锋. 基于R/S分析法与分形理论的围岩变形特征研究. 四川大学学报(工程科学版),2010,42(3):43-48.
罗 林,左昌群,赵 连,等. 基于BP神经网络和R/S分析的隧道仰坡沉降变形预报预测. 施工技术,2014,(11):80-84.
孙洪泉. 分形几何及其分形插值研究. 河北工业大学学报, 2002,(1): 56-60.

基金

国家自然科学基金项目(41202201,41102196,51379194);中央高校基本科研业务费专项资金项目(CUGL110215);国土资源部公益性行业科研专项经费资助项目(201211039)

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