Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating
The application of the neural network method in health monitoring and structural system identification has received extensive attention. A reasonable neural network structure is very important for its performance. This paper takes the pedestrian bridge of the Xingfu intersection in Urumqi, China, as...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/1057422 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832562204236316672 |
|---|---|
| author | Rui Zhao Yuhang Wu Zehua Feng |
| author_facet | Rui Zhao Yuhang Wu Zehua Feng |
| author_sort | Rui Zhao |
| collection | DOAJ |
| description | The application of the neural network method in health monitoring and structural system identification has received extensive attention. A reasonable neural network structure is very important for its performance. This paper takes the pedestrian bridge of the Xingfu intersection in Urumqi, China, as the research object and uses MIDAS/Civil to establish a finite element analysis model. Taking the natural vibration frequency obtained from the dynamic test of the actual bridge as the target, two kinds of neural networks are used to predict the structural material parameters. An appropriate bridge model correction method is selected by comparing the prediction results of the BP neural network and the GRNN. The test results show that the pedestrian bridge model based on MIDAS/Civil has a high accuracy, but it still does not meet the actual needs. The modified model based on the BP neural network is close to the actual measured results, and a more accurate finite element analysis model can be established by this method, which makes the modified model closer to the real stress state of the structure. |
| format | Article |
| id | doaj-art-9253f0f3806b4bf7acce50884d478f0a |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-9253f0f3806b4bf7acce50884d478f0a2025-02-03T01:23:09ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/1057422Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model UpdatingRui Zhao0Yuhang Wu1Zehua Feng2School of Civil Engineering and ArchitectureSchool of Civil Engineering and ArchitectureSchool of Civil Engineering and ArchitectureThe application of the neural network method in health monitoring and structural system identification has received extensive attention. A reasonable neural network structure is very important for its performance. This paper takes the pedestrian bridge of the Xingfu intersection in Urumqi, China, as the research object and uses MIDAS/Civil to establish a finite element analysis model. Taking the natural vibration frequency obtained from the dynamic test of the actual bridge as the target, two kinds of neural networks are used to predict the structural material parameters. An appropriate bridge model correction method is selected by comparing the prediction results of the BP neural network and the GRNN. The test results show that the pedestrian bridge model based on MIDAS/Civil has a high accuracy, but it still does not meet the actual needs. The modified model based on the BP neural network is close to the actual measured results, and a more accurate finite element analysis model can be established by this method, which makes the modified model closer to the real stress state of the structure.http://dx.doi.org/10.1155/2022/1057422 |
| spellingShingle | Rui Zhao Yuhang Wu Zehua Feng Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating Shock and Vibration |
| title | Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating |
| title_full | Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating |
| title_fullStr | Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating |
| title_full_unstemmed | Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating |
| title_short | Research for Pedestrian Steel Bridge Design of Neural Network in Structural Model Updating |
| title_sort | research for pedestrian steel bridge design of neural network in structural model updating |
| url | http://dx.doi.org/10.1155/2022/1057422 |
| work_keys_str_mv | AT ruizhao researchforpedestriansteelbridgedesignofneuralnetworkinstructuralmodelupdating AT yuhangwu researchforpedestriansteelbridgedesignofneuralnetworkinstructuralmodelupdating AT zehuafeng researchforpedestriansteelbridgedesignofneuralnetworkinstructuralmodelupdating |