Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor
To further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, o...
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MDPI AG
2020-02-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/20/4/1187 |
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author | Shuai Shao Zhixiang Zhou Guojun Deng Peng Du Chuanyi Jian Zhongru Yu |
author_facet | Shuai Shao Zhixiang Zhou Guojun Deng Peng Du Chuanyi Jian Zhongru Yu |
author_sort | Shuai Shao |
collection | DOAJ |
description | To further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, owing to its economic, credible, high frequency, and holographic advantages. This study validates a proposed holographic visual sensor and algorithms in a computer-vision-based full-field non-contact displacement and vibration measurement. Using an automatic camera patrol experimental device, original segmental dynamic and static video monitoring data of a model bridge under various damage/activities were collected. According to the temporal and spatial characteristics of the series data, the holographic geometric morphology tracking algorithm was introduced. Additionally, the feature points set of the structural holography geometry and the holography feature contours were established. Experimental results show that the holographic visual sensor and the proposed algorithms can extract an accurate holographic full-field displacement signal, and factually and sensitively accomplish vibration measurement, while accurately reflecting the real change in structural properties under various damage/action conditions. The proposed method can serve as a foundation for further research on digital twins for large-scale structures, structural condition assessment, and intelligent damage identification. |
first_indexed | 2024-04-11T14:09:01Z |
format | Article |
id | doaj.art-33db5574bb0c42d08041c2bc30632cf2 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-04-11T14:09:01Z |
publishDate | 2020-02-01 |
publisher | MDPI AG |
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series | Sensors |
spelling | doaj.art-33db5574bb0c42d08041c2bc30632cf22022-12-22T04:19:46ZengMDPI AGSensors1424-82202020-02-01204118710.3390/s20041187s20041187Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual SensorShuai Shao0Zhixiang Zhou1Guojun Deng2Peng Du3Chuanyi Jian4Zhongru Yu5School of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaCollege of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518061, ChinaSchool of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaSchool of Civil Engineering, Chongqing Jiaotong University, Chongqing 400074, ChinaTo further improve the precision and efficiency of structural health monitoring technology and the theory of large-scale structures, full-field non-contact structural geometry morphology monitoring is expected to be a breakthrough technology in structural safety state monitoring and digital twins, owing to its economic, credible, high frequency, and holographic advantages. This study validates a proposed holographic visual sensor and algorithms in a computer-vision-based full-field non-contact displacement and vibration measurement. Using an automatic camera patrol experimental device, original segmental dynamic and static video monitoring data of a model bridge under various damage/activities were collected. According to the temporal and spatial characteristics of the series data, the holographic geometric morphology tracking algorithm was introduced. Additionally, the feature points set of the structural holography geometry and the holography feature contours were established. Experimental results show that the holographic visual sensor and the proposed algorithms can extract an accurate holographic full-field displacement signal, and factually and sensitively accomplish vibration measurement, while accurately reflecting the real change in structural properties under various damage/action conditions. The proposed method can serve as a foundation for further research on digital twins for large-scale structures, structural condition assessment, and intelligent damage identification.https://www.mdpi.com/1424-8220/20/4/1187structural geometry monitoringcomputer-vision-based measurement technologybridge safetyholographic visual sensordense full-field measurementdigital twins |
spellingShingle | Shuai Shao Zhixiang Zhou Guojun Deng Peng Du Chuanyi Jian Zhongru Yu Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor Sensors structural geometry monitoring computer-vision-based measurement technology bridge safety holographic visual sensor dense full-field measurement digital twins |
title | Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor |
title_full | Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor |
title_fullStr | Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor |
title_full_unstemmed | Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor |
title_short | Experiment of Structural Geometric Morphology Monitoring for Bridges Using Holographic Visual Sensor |
title_sort | experiment of structural geometric morphology monitoring for bridges using holographic visual sensor |
topic | structural geometry monitoring computer-vision-based measurement technology bridge safety holographic visual sensor dense full-field measurement digital twins |
url | https://www.mdpi.com/1424-8220/20/4/1187 |
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