Time series analysis of tunnel displacement based on ARMA model

The displacement monitoring of tunnel plays an important role in assessing surrounding rock's stability and supporting structure's rationality during using new Austrian tunneling method(NATM).In light of the fact that auto regressive(AR) model is usually adopted to analyze displacement of tunnel with time series, which avoids nonlinear estimation but leads to lower fitting accuracy and poorer model's practicality.The auto regressive moving average(ARMA) model which has higher accuracy and good practicability is reviewed;its common parameter estimate methods is introduced;and a parametric estimation approximate linear method of ARMA model is presented in light of the inconvenience of the nonlinear parameter estimation of ARMA model, which linearizes nonlinear estimation through expanding residues with Taylor series in first order, and then estimate final parameter with linear least square method.Using the method of time series to model and analyze the displacement monitoring data of Nanshan tunnel in Dazu county of Chongqing, the prediction is in agreement with actual measurements;it is proved that the method is basically feasible.