Combination forecast model for concrete dam displacement considering residual correction. (January 2019)

• Record Type: Journal Article
• Authors: Wei, Bowen; Yuan, Dongyang; Li, Huokun; Xu, Zhenkai
• Other Names: Nguyen Andy guest-editor.; Chan Tommy HT guest-editor.; Zhu Xinqun guest-editor.
• Is Part Of: Structural health monitoring. Volume 18:Number 1(2019)
• Page Start: 232
• Page End: 244
• Publication Date: 2019-01
• Subjects: Concrete dam -- displacement forecast -- fitting residual sequence -- back propagation neural network -- autoregressive integrated moving average; Structural health monitoring -- Periodicals; Structural stability -- Periodicals; Strength of materials -- Periodicals; Nondestructive testing -- Periodicals; Constructions -- Stabilité -- Périodiques; Résistance des matériaux -- Périodiques; Contrôle non destructif -- Périodiques; Electronic journals; 624.17
• DOI: 10.1177/1475921717748608
• Languages: English
• ISSNs: 1475-9217

Abstract

In conventional dam displacement monitoring models, forecast precision is below the standard, the fitting residual sequence contains chaotic components, and information mining of dam prototype observation data is limited. In consideration of the chaotic characteristics of the fitting residual sequence in regression model, the multi-scale wavelet analysis is used to decompose and reconstruct the residual sequence in this study; back propagation neural network and autoregressive integrated moving average model are used to forecast the reconstructed residual sequence by identifying the high-frequency and low-frequency characteristics of signals. By superimposing the residual forecast value with the forecast value of regression model, the combination forecast model for concrete dam displacement considering residual correction is proposed. Examples show that, compared with conventional models, the proposed combination model is better in fitting precision and convergence speed. Forecast capability is significantly improved for dam displacement forecast when effective components contained in residual sequence are considered. A new method of displacement forecast for high slope and other hydraulic structures is presented.