Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models
In this article, an approach for using structural health monitoring coupled extreme stress data in dynamic extreme stress prediction of steel bridges is presented, where the coupled extreme stress data means the extreme stress data with dynamicity, randomness, and trend. Firstly, the modeling proces...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8712907 |
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| _version_ | 1832555062666199040 |
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| author | Xueping Fan Zhipeng Shang Guanghong Yang Xiaoxiong Zhao Yuefei Liu |
| author_facet | Xueping Fan Zhipeng Shang Guanghong Yang Xiaoxiong Zhao Yuefei Liu |
| author_sort | Xueping Fan |
| collection | DOAJ |
| description | In this article, an approach for using structural health monitoring coupled extreme stress data in dynamic extreme stress prediction of steel bridges is presented, where the coupled extreme stress data means the extreme stress data with dynamicity, randomness, and trend. Firstly, the modeling processes about dynamic coupled linear models (DCLM) are provided based on a supposed coupled time series; furthermore, the dynamic probabilistic recursion processes about DCLM are given with Bayes method; secondly, the monitoring dynamic coupled extreme stress data is taken as a time series, historical monitoring coupled extreme stress data-based DCLM and the corresponding Bayesian probabilistic recursion processes are given for predicting bridge extreme stresses; furthermore, the monitoring mechanism is provided for monitoring the prediction precision of DCLM; finally, the monitoring coupled extreme stress data of a steel bridge is used to illustrate the proposed approach which can provide the foundations for bridge reliability prediction and assessment. |
| format | Article |
| id | doaj-art-a42cfa9c81ea4e61983ba502b06aa717 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-a42cfa9c81ea4e61983ba502b06aa7172025-02-03T05:49:40ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/87129078712907Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear ModelsXueping Fan0Zhipeng Shang1Guanghong Yang2Xiaoxiong Zhao3Yuefei Liu4School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, ChinaSchool of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, ChinaSchool of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, ChinaSchool of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, ChinaSchool of Civil Engineering and Mechanics, Lanzhou University, Lanzhou 730000, ChinaIn this article, an approach for using structural health monitoring coupled extreme stress data in dynamic extreme stress prediction of steel bridges is presented, where the coupled extreme stress data means the extreme stress data with dynamicity, randomness, and trend. Firstly, the modeling processes about dynamic coupled linear models (DCLM) are provided based on a supposed coupled time series; furthermore, the dynamic probabilistic recursion processes about DCLM are given with Bayes method; secondly, the monitoring dynamic coupled extreme stress data is taken as a time series, historical monitoring coupled extreme stress data-based DCLM and the corresponding Bayesian probabilistic recursion processes are given for predicting bridge extreme stresses; furthermore, the monitoring mechanism is provided for monitoring the prediction precision of DCLM; finally, the monitoring coupled extreme stress data of a steel bridge is used to illustrate the proposed approach which can provide the foundations for bridge reliability prediction and assessment.http://dx.doi.org/10.1155/2020/8712907 |
| spellingShingle | Xueping Fan Zhipeng Shang Guanghong Yang Xiaoxiong Zhao Yuefei Liu Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models Advances in Civil Engineering |
| title | Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models |
| title_full | Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models |
| title_fullStr | Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models |
| title_full_unstemmed | Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models |
| title_short | Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models |
| title_sort | incorporation of structural health monitoring coupled data in dynamic extreme stress prediction of steel bridges using dynamic coupled linear models |
| url | http://dx.doi.org/10.1155/2020/8712907 |
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