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隧道下穿时基于傅里叶时间序列预测临近结构沉降发展
A forecasting method based on Fourier time series for short-term settlements in adjacent structures during an under-passing shield tunnel construction

DOI: 10.7631/issn.1000-2243.2015.02.0238

Keywords: 沉降预测 短期沉降 时间序列 傅里叶级数 隧道穿越
settlement forecasting short-term settlement time series Fourier series under-passing tunnel

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Abstract:

隧道下穿临近结构时,目前仅能基于现有沉降判定结构是否安全,缺乏对未来短期内沉降发展的预测方法. 通过测量某隧道右线下穿临近某水库时水库逐小时的沉降,分析得出水库短期沉降主要由隧道下穿引起的趋势项和每日温度波动导致的周期项组成,并根据以上特点提出一种基于傅里叶时间序列的结构短期沉降预测方法. 该方法采用傅里叶级数和线性函数对周期项和趋势项分别进行拟合,并通过数据的新陈代谢保证一旦沉降发生突变后,该方法所得预测沉降对突变具有较好的灵敏度. 采用该水库在同一隧道左线下穿时的沉降实测数据对该方法和GM(1,1)灰色模型的预测精度进行比较. 结果表明,该方法的预测精度高于GM(1,1)灰色模型.
During an under-passing shield tunnel construction,the safety of the adjacent structures is only determined by existing structural settlements. It is lack of the forecasting method for the future short-term increment of the structural settlements. The hourly settlements of a reservoir suffering from an adjacent under-passing right shield tunnel construction has been measured and analyzed. Results show that the future short-term settlement can be divided into a trend part and a periodic part,which are caused by the adjacent under-passing shield tunnel construction and daily environmental temperature cycling,respectively. Then this paper proposes a forecasting method based on Fourier time series for short-term settlements,which uses a first-order transformation and the Fourier expansion to fit the trend part and the periodical part. And self-correcting process is including in this method to ensure that the forecasting settlements are sensitive to the sudden changes in settlements. At last,a series of practical monitoring settlements of the same reservoir suffering from the adjacent under-passing left shield tunnel construction are used to compare the forecasting precision between the proposed method and the gray model GM(1,1). Results from the comparison show that the forecasting settlements from the proposed method are more accurate than those from the gray model GM(1,1)

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