Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement
In conventional structural health monitoring (SHM), the installation of sensors and data acquisition devices will affect the regular operation of structures to a certain extent and is also expensive. In order to overcome these shortcomings, the computer vision- (CV-) based method has been introduced...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/5444101 |
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| author | Tao Liu Yu Lei Yibing Mao |
| author_facet | Tao Liu Yu Lei Yibing Mao |
| author_sort | Tao Liu |
| collection | DOAJ |
| description | In conventional structural health monitoring (SHM), the installation of sensors and data acquisition devices will affect the regular operation of structures to a certain extent and is also expensive. In order to overcome these shortcomings, the computer vision- (CV-) based method has been introduced into SHM, and its practical applications are increasing. In this paper, CV-based SHM methods such as template matching and Hough circle transform are described. In order to improve the accuracy of pixel localization, the subpixel localization refinement method is introduced. The displacement monitoring experiment of an aluminum alloy cantilever with three targets is conducted by using the two CV-based SHM methods and the laser displacement sensors simultaneously. The displacement monitoring results of CV-based methods agree well with those measured by the laser transducer system in the time domain. After that, the first two modes of the cantilever are identified from the monitoring results. In addition, the experimental modes identified from the monitoring data and those calculated from the finite element model are also consistent. Therefore, the developed CV-based methods can obtain accurate displacement results in both time and frequency domains, which could be applied to complex structures with more monitoring targets. |
| format | Article |
| id | doaj-art-dfa154c1005345f0894e274689ede1be |
| institution | Kabale University |
| issn | 1687-8094 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-dfa154c1005345f0894e274689ede1be2025-02-03T01:20:07ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/5444101Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization RefinementTao Liu0Yu Lei1Yibing Mao2Department of Civil EngineeringDepartment of Civil EngineeringTechnology Research Center for Reinforcement and Translation of BuildingsIn conventional structural health monitoring (SHM), the installation of sensors and data acquisition devices will affect the regular operation of structures to a certain extent and is also expensive. In order to overcome these shortcomings, the computer vision- (CV-) based method has been introduced into SHM, and its practical applications are increasing. In this paper, CV-based SHM methods such as template matching and Hough circle transform are described. In order to improve the accuracy of pixel localization, the subpixel localization refinement method is introduced. The displacement monitoring experiment of an aluminum alloy cantilever with three targets is conducted by using the two CV-based SHM methods and the laser displacement sensors simultaneously. The displacement monitoring results of CV-based methods agree well with those measured by the laser transducer system in the time domain. After that, the first two modes of the cantilever are identified from the monitoring results. In addition, the experimental modes identified from the monitoring data and those calculated from the finite element model are also consistent. Therefore, the developed CV-based methods can obtain accurate displacement results in both time and frequency domains, which could be applied to complex structures with more monitoring targets.http://dx.doi.org/10.1155/2022/5444101 |
| spellingShingle | Tao Liu Yu Lei Yibing Mao Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement Advances in Civil Engineering |
| title | Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement |
| title_full | Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement |
| title_fullStr | Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement |
| title_full_unstemmed | Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement |
| title_short | Computer Vision-Based Structural Displacement Monitoring and Modal Identification with Subpixel Localization Refinement |
| title_sort | computer vision based structural displacement monitoring and modal identification with subpixel localization refinement |
| url | http://dx.doi.org/10.1155/2022/5444101 |
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