浅谈基于随机模型的隧道施工引起地面沉降的小波分析

目前预测隧道施工引起的地面随时间变化的沉降过程的方法有一定的局限性，这种局限性是由于测量误差的存在而引起的。在这项研究中，研究的方法是用数据建立一个随机模型的时间序列，而测量误差被作为是一个按正态分布的随机序列。另外，按正态性检验和方差分析的方法，被用来验证沉降数据过滤部分的特性与测量数据的误差是否是一致的。这样，当采用离散小波变换时，就可以确定小波基及分解水平的最佳选择。利用一个工程实例去验证了这种假设，并证明了这种方法的可行性。

Wavelet Analysis for Tunneling -induced Ground Settlement Based on a Stochastic Model

Methods the forecast the ground settlement induced by tunnel construction process with time - varying has some limitations, this limitation is due to measurement errors. In this study, research method is using the data to establish a stochastic model of time series, and the measurement error was regarded as a basic of normal distribution random sequence. In addition, analytical methods according to test and variance of normality, were used to validate the settlement characteristics and measurement error data filter portion is consistent. So, when using the discrete wavelet transform, we can determine the best choice of wavelet base and the decomposition level. In this paper, using an engineering example to verify the hypothesis, and proved the feasibility of this approach.