A combination model for evaluating deformation regional characteristics of arch dams using time series clustering and residual correction. (1st November 2022)

• Record Type: Journal Article
• Authors: Chen, Huangdong; Chen, Xudong; Guan, Junyi; Zhang, Xuan; Guo, Jinjun; Yang, Guang; Xu, Bo
• Is Part Of: Mechanical systems and signal processing. Volume 179(2022)
• Publication Date: 2022-11-01
• Subjects: Structural health monitoring -- Arch dam -- BSD-DTW clustering -- Combination model -- Residual correction -- Regional characteristics; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109397
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: BSD-DTW clustering is applied to the classification of arch dam deformation measuring points. Panel data model and Holt–Winters model are combined to build prediction model of arch dam deformation. The regional characteristics of arch dam deformation is investigated. Residual correction is an effective method for exploring potential deformation laws. Abstract: Deformation monitoring models developed for the relationship between influencing factors and deformation are widely used in dam structural health monitoring. Because of the integrity of the arch dam, every part of the dam is interrelated and interactive. The regional characteristics of arch dam deformation have not been fully considered in the current arch dam monitoring model. The main purpose of this paper is to develop and verify a combination model for arch dam deformation considering regional characteristics. The arch dam measuring points are first clustered according to the similarity indicator of Bilateral Slope-based Distance and Dynamic Time Warping algorithm (BSD-DTW) between their measured deformation time series. Then the BSD-DTW clustering-based panel data model is established for each clustered zone to reflect the similarities and differences of deformation laws in different regions. Considering intra-regional differences in measuring point deformation, the Holt-Winters model is utilized to identify the potential features contained in panel data model's residual series. Finally, a combination model is constructed by superimposing the predicted value of the Holt-Winters model on the predicted value of the BSD-DTW clustering-based panel data model. The engineering example demonstrates that the BSD-DTW clustering method is a more reasonable method for arch dam regional zoning, and the combination model with residual correction can fully explore the deformation regional characteristics of each measuring point and has higher prediction accuracy, making it an effective analysis method for structural deformation of arch dams.