Dynamic Characteristics Identification of an Arch Dam Model via the Phase-Based Video Processing
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pISSN 1226-7988, eISSN 1976-3808 www.springer.com/12205
DOI 10.1007/s12205-020-0400-z
Hydraulic Engineering
Dynamic Characteristics Identification of an Arch Dam Model via the Phase-Based Video Processing Qi Li
a
, Gaohui Wang
b
, Aral Sarrafi
c
, Xinqiang Niua, Wenbo Lu
b
, and Zhu Mao
c
a
Changjiang Institute of Survey, Planning, Design and Research, Wuhan 430010, China State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China c Structural Dynamics and Acoustic Systems Laboratory, University of Massachusetts Lowell, Lowell, MA 01854, USA b
ARTICLE HISTORY
ABSTRACT
Received 4 March 2020 Accepted 6 August 2020 Published Online 4 November 2020
In recent years, the extraction of structural dynamic characteristics by using phase-based video processing has attracted considerable attention. Edge detection routine is oftentimes employed to obtain the quantified operational deflection shape (ODS) vectors of structures. However, this approach is unreliable because of intensive human supervision and correction. To reduce operational uncertainty, a hybrid computer-vision-based approach called edge detection-region labeling, which involves vision sensor preparation, bottom-hat filtering, edge detection, hole filling, and region labeling, was presented in this work to extract the quantified ODS’s. The performance of this method was firstly evaluated by conducting a lab-scale cantilever beam test and subsequently the phase-based video processing was applied to extract the dynamic characteristics of an arch dam model. The operational modal analysis (OMA) test was conducted on the benchmark dam model. In-plane motions of the dam were captured and processed to identify the natural frequencies of the dam. The structural ODS’s were quantified using the proposed method. A comparison of the modal parameters of the dam identified from the video data with those obtained in the OMA test revealed that the two sets of results were consistent, and the video processing approach was able to bypass the requirement of human supervision, which facilitates the application of the phase-based video processing for complex structures.
KEYWORDS Phase-based video processing Arch dam Dynamic characteristics Operational modal analysis Computer vision
1. Introduction Dams are constructed for various purposes, including hydroelectric power generation, flood control, navigation, irrigation, and drinking water supply. Concrete arch dams, one of the possible means of impoundment, can transmit most of the water and sediment pressure to the bedrock along the river valley with the help of the arch action. These dams have been proved to be effective and beneficial. However, over the course of their entire service life, arch dams are subjected to diverse environmental loadings, such as floods, earthquakes, and temperature variations. In addition, age-related deterioration and human factors, such as war and terrorist attacks, severely threaten the safety of arch dams. Multiple catastrophic
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