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Poster P-3-5-14: Seismic damage identification of high arch dams based on an unsupervised deep learning approach

XVIII IWRA World Water Congress Beijing China 2023
Sub-theme 5: Establishing Sustainable Water Infrastructures
Author(s): Xiangyu Cao, Jianyun Chen, Lei Tang

Xiangyu Caoa, Jianyun Chenb, Lei Tanga

a Nanjing Hydraulic Research Institute, Nanjing 210029, People’s Republic of China

b School of Hydraulic Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, People’s Republic of China


Poster: PDF

Abstract

Objectives of the study

Arch dams have been widely constructed around the world due to the advantages of economy, safety and reliability. The strong uncertainty of earthquakes makes it possible for arch dams to be subjected to over-designed earthquakes, which may lead to extremely serious casualties and property losses. In actual concrete arch dam engineering scenarios, the dynamic data obtained by the health monitoring system of an arch dam are incomplete. The data acquired typically depend on the state of the dam structure, that is, whether it is intact or incomplete. Accordingly, the formulation of an accurate, efficient, and intelligent damage warning and identification model for concrete arch dams is necessary to ensure infrastructure safety.

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