Segmented modeling method of dam displacement based on BEAST time series decomposition

被引：25
作者：
Xu, Xiaoyan
Yang, Jie
Ma, Chunhui [1 ]
Qu, Xudong
Chen, Jiamin
Cheng, Lin
机构：
[1] Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg, Xian 710048, Peoples R China
来源：
MEASUREMENT | 2022年 / 202卷
基金：
中国国家自然科学基金;
关键词：
Segmented modeling; Bayes; Time series decomposition; Dam safety monitoring; PREDICTION MODEL;
D O I：
10.1016/j.measurement.2022.111811
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The dam and its operating environment are complex and uncertain and often show many different operating rules during its operating period. In this paper, firstly, the principal component analysis is used to extract the comprehensive displacement of multiple measuring points; Then, the comprehensive displacement is decom-posed into seasonal and trend parts by using the Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) method, and the change of its change law is quantitatively analyzed; Finally, the influence of each environmental quantity on the dam displacement is quantified by selecting the change point reasonably. The method proposed in this paper is verified by the quantitative analysis of the displacement law of multiple measuring points of an earth rock dam in different periods. The research results provide strong technical support for better analysis of the evolution process of dam deformation behavior and quantitative interpretation of dam deformation mechanism.
引用
收藏
页数：17
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