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 • 上一篇    下一篇

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   

  1. 中国地质大学武汉 工程学院, 武汉 430074
  • 收稿日期:2015-01-19 出版日期:2016-04-01 发布日期:2016-04-08
  • 作者简介:左昌群(1981-),女,湖北荆州人,讲师,博士,主要从事岩土工程研究,(电话)13554111141(电子信箱)helenzz@126.com。
  • 基金资助:
    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)

Analysis and Prediction of Tunnel Surface SubsidenceBased on Fractal Theory

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

  1. Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
  • Received:2015-01-19 Online:2016-04-01 Published:2016-04-08

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。

关键词: 地表沉降, 变形时间序列, 分形理论, Hurst指数, 分形插值

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.

Key words: ground surface subsidence, deformation time series, fractal theory, Hurst index, fractal interpolation

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