Lieyun Ding, Ling Ma, Hanbin Luo, Minghui Yu, Xianguo Wu

ABSTRACT:

Current practice in predicting tunneling-induced ground settlement has some limitations in describingthe time-dependent settlement process due to the existence of measurement error. In this study, settlementdata was considered as time series by establishing a stochastic model, while measurement errorwas regarded as a stationary and normally distributed stochastic process. Furthermore, Wavelet Analysiswas introduced to filter the measurement error and extract the actual settlement value, which is similarto denoising in signal processing. In addition, methods such as the unit root test, normality test andANOVA, were used to testify whether the characteristics of the filtered part of settlement data were consistentwith those of measurement error. As a result, an optimal selection of wavelet basis and decompositionlevel could be made when using Discrete Wavelet Transform. Finally, extensive instrumentationdata obtained from a real tunnel project supported our model hypothesis and proved the feasibility ofthis approach, and decomposing at level 4 with wavelet D16 was proved to achieve the best performance.

Keywords：Ground settlement;   Stochastic model;   Wavelet Analysis;   Time-series analysis;   NATM