Bridge Structural Damage Identification Technique Based on BPNN and Vehicle-bridge Interaction Analysis
During the use of bridges, the traditional method of detecting the bridge condition cannot be continuously monitored and maintained. To address this problem, the study proposed a damage identification method based on the interaction of back propagation neural network and vehicle-bridge interaction....
Saved in:
| Main Authors: | Lingling Li, Yibo Zhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Electronic Journals for Science and Engineering - International
2025-07-01
|
| Series: | Electronic Journal of Structural Engineering |
| Subjects: | |
| Online Access: | https://ejsei.com/EJSE/article/view/774 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Analysis of Rail Vehicle Axle Strength and Fatigue Crack Propagation Life
by: LI Rui-xia, et al.
Published: (2013-01-01) -
EXPERIMENTAL RESEARCH OF THE FRIABLE LOAD OFFSETS’ EFFECT ON THE VEHICLES’ AXIAL CARGO CHANGING
by: E. R. Kirkolup, et al.
Published: (2019-04-01) -
Detection of Gas6/AXL complex and its expression changes in patients with ST-segment elevation myocardial infarction
by: Zhao Yin, et al.
Published: (2025-08-01) -
Dual targeting of TAM receptors Tyro3, Axl, and MerTK: Role in tumors and the tumor immune microenvironment
by: Kai-Hung Wang, et al.
Published: (2021-01-01) -
Research on the Influence of Axle Deviation Angle on Riding Performance of Autonomous-Rail Rapid Trams
by: YU Juan, et al.
Published: (2024-12-01)