Abstract: The total deformation of concrete dam can be attributed to the deformation caused by water pressure, temperature and time, among which the deformations caused by water pressure and temperature are reflected as periodic components, while the aging deformation as trend component. In this paper, a combinatorial deformation prediction model for concrete dam is established by integrating wavelet decomposition, Even Grey Model (EGM), Periodic Extension (PE), and Autoregressive Integrated Moving Average (ARIMA) model. Wavelet is employed to decompose the trend items and periodic items in the time series of dam deformation; EGM for the effective prediction of trend term, and PE model for periodic term; ARIMA model is adopted for the prediction of residuals of EGM and PE model. An engineering case study verifies the effectiveness of the present model. The results show that the time series of dam deformation can be fitted and predicted effectively by this combined model, in which the variation law of each deformation component of the dam is considered. The fitting accuracy and prediction accuracy of the combined model are both superior to those of traditional statistical model.

Key words: concrete dam, deformation prediction, wavelet analysis, EGM(1,1), periodic extension model, ARIMA