Early-Warning Method of Train Running Safety of a High-Speed Railway Bridge Based on Transverse Vibration Monitoring
Author(s): |
You-liang Ding
Peng Sun Gao-xin Wang Yong-sheng Song Lai-Yi Wu Qing Yue Ai-Qun Li |
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Medium: | journal article |
Language(s): | English |
Published in: | Shock and Vibration, 2015, v. 2015 |
Page(s): | 1-9 |
DOI: | 10.1155/2015/518689 |
Abstract: |
Making use of long-term transverse vibration monitoring data of DaShengGuan Bridge, the early-warning method of train running safety of the high-speed railway bridge is established by adopting principal component analysis (PCA) method. Firstly, the root mean square (RMS) of the transverse acceleration of the main girder is used as the monitoring parameter for the train running safety. The correlation model between the RMS values measured from different positions is further adopted as the evaluating model for the train running safety. Finally, the effects of the environmental changes on the evaluating model are eliminated using the PCA method and the warning index for the train running safety is further constructed. The analysis results show that the correlation between the RMS values of the accelerations from different measuring positions on the main girder can be analyzed by a quadratic polynomial fitting model. The PCA method can effectively remove the environmental effects on the quadratic polynomial fitting model. The proposed warning method provides a good capability for detecting the abnormal changes of the measured transverse accelerations and hence it is suitable for early-warning of the train running safety. |
Copyright: | © 2015 You-Liang Ding, Peng Sun, Gao-Xin Wang, Yong-Sheng Song, Lai-Yi Wu, Qing Yue, Ai-Qun Li |
License: | This creative work has been published under the Creative Commons Attribution 3.0 Unported (CC-BY 3.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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28/05/2022 - Last updated on:
01/06/2022