Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes
This study applied the kriging model and particle swarm optimization (PSO) algorithm for the dynamic model updating of bridge structures using the higher vibration modes under large-amplitude initial conditions. After addressing the higher mode identification theory using time-domain operational mod...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-06-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/6/1879 |
| _version_ | 1811300820403093504 |
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| author | Shiqiang Qin Yazhou Zhang Yun-Lai Zhou Juntao Kang |
| author_facet | Shiqiang Qin Yazhou Zhang Yun-Lai Zhou Juntao Kang |
| author_sort | Shiqiang Qin |
| collection | DOAJ |
| description | This study applied the kriging model and particle swarm optimization (PSO) algorithm for the dynamic model updating of bridge structures using the higher vibration modes under large-amplitude initial conditions. After addressing the higher mode identification theory using time-domain operational modal analysis, the kriging model is then established based on Latin hypercube sampling and regression analysis. The kriging model performs as a surrogate model for a complex finite element model in order to predict analytical responses. An objective function is established to express the relative difference between analytically predicted responses and experimentally measured ones, and the initial finite element (FE) model is hereinafter updated using the PSO algorithm. The Jalón viaduct—a concrete continuous railway bridge—is applied to verify the proposed approach. The results show that the kriging model can accurately predict the responses and reduce computational time as well. |
| first_indexed | 2024-04-13T06:57:03Z |
| format | Article |
| id | doaj.art-82b2e698df0646d89264055c6e41ce51 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:57:03Z |
| publishDate | 2018-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-82b2e698df0646d89264055c6e41ce512022-12-22T02:57:13ZengMDPI AGSensors1424-82202018-06-01186187910.3390/s18061879s18061879Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration ModesShiqiang Qin0Yazhou Zhang1Yun-Lai Zhou2Juntao Kang3School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, ChinaDepartment of Civil and Environmental Engineering, National University of Singapore, 2 Engineering Drive 2, Singapore 117576, SingaporeSchool of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan 430070, ChinaThis study applied the kriging model and particle swarm optimization (PSO) algorithm for the dynamic model updating of bridge structures using the higher vibration modes under large-amplitude initial conditions. After addressing the higher mode identification theory using time-domain operational modal analysis, the kriging model is then established based on Latin hypercube sampling and regression analysis. The kriging model performs as a surrogate model for a complex finite element model in order to predict analytical responses. An objective function is established to express the relative difference between analytically predicted responses and experimentally measured ones, and the initial finite element (FE) model is hereinafter updated using the PSO algorithm. The Jalón viaduct—a concrete continuous railway bridge—is applied to verify the proposed approach. The results show that the kriging model can accurately predict the responses and reduce computational time as well.http://www.mdpi.com/1424-8220/18/6/1879dynamic model updatingkriging modelparticle swarm optimizationhigher modesbridge structure |
| spellingShingle | Shiqiang Qin Yazhou Zhang Yun-Lai Zhou Juntao Kang Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes Sensors dynamic model updating kriging model particle swarm optimization higher modes bridge structure |
| title | Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes |
| title_full | Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes |
| title_fullStr | Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes |
| title_full_unstemmed | Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes |
| title_short | Dynamic Model Updating for Bridge Structures Using the Kriging Model and PSO Algorithm Ensemble with Higher Vibration Modes |
| title_sort | dynamic model updating for bridge structures using the kriging model and pso algorithm ensemble with higher vibration modes |
| topic | dynamic model updating kriging model particle swarm optimization higher modes bridge structure |
| url | http://www.mdpi.com/1424-8220/18/6/1879 |
| work_keys_str_mv | AT shiqiangqin dynamicmodelupdatingforbridgestructuresusingthekrigingmodelandpsoalgorithmensemblewithhighervibrationmodes AT yazhouzhang dynamicmodelupdatingforbridgestructuresusingthekrigingmodelandpsoalgorithmensemblewithhighervibrationmodes AT yunlaizhou dynamicmodelupdatingforbridgestructuresusingthekrigingmodelandpsoalgorithmensemblewithhighervibrationmodes AT juntaokang dynamicmodelupdatingforbridgestructuresusingthekrigingmodelandpsoalgorithmensemblewithhighervibrationmodes |