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Real‐time identification of time‐varying tension in stay cables by monitoring cable transversal acceleration
Stay cables are critical components in bridges. However, stay cables suffer from severe fatigue damage. Therefore, a monitoring technique to obtain the time history of the tension in stay cables is important. Because the acceleration of stay cables is readily measurable, approaches to identify cable tension based on frequency analysis and monitored cable acceleration have been widely investigated and used in practice. However, this type of approach can only identify a time‐invariant tension of a stay cable over a specified duration, not the time‐varying tension. This paper proposes an approach to identify the time‐varying tension of stay cables by monitoring cable accelerations. The tension variation in stay cables is caused by vehicles passing over the bridge. The real‐time identification algorithm that determines the time‐varying tension of stay cables is proposed using an extended Kalman filter based on both the transversal monitored acceleration at a single location on the cable and the monitored wind speed on the bridge, where the time‐varying tension is a state variable that is identified. A stay cable from the Nanjing Yangtze River No. 3 Bridge was used for the numerical study. The time‐varying tension of the stay cable can be identified when either a single vehicle or multiple vehicles pass over the bridge. The robustness of the proposed approach is also investigated through deviations in the initial tension, initial displacement, and velocity of the stay cable. An experiment was conducted on a scaled stay cable with time‐varying tension excited by wind. The time‐varying cable tension of the cable was identified by the proposed approach and compared with the real time‐varying cable tension. The identification accuracy and robustness of the proposed approach is verified through the experiment and numerical study. Copyright © 2013 John Wiley & Sons, Ltd.
Real‐time identification of time‐varying tension in stay cables by monitoring cable transversal acceleration
Stay cables are critical components in bridges. However, stay cables suffer from severe fatigue damage. Therefore, a monitoring technique to obtain the time history of the tension in stay cables is important. Because the acceleration of stay cables is readily measurable, approaches to identify cable tension based on frequency analysis and monitored cable acceleration have been widely investigated and used in practice. However, this type of approach can only identify a time‐invariant tension of a stay cable over a specified duration, not the time‐varying tension. This paper proposes an approach to identify the time‐varying tension of stay cables by monitoring cable accelerations. The tension variation in stay cables is caused by vehicles passing over the bridge. The real‐time identification algorithm that determines the time‐varying tension of stay cables is proposed using an extended Kalman filter based on both the transversal monitored acceleration at a single location on the cable and the monitored wind speed on the bridge, where the time‐varying tension is a state variable that is identified. A stay cable from the Nanjing Yangtze River No. 3 Bridge was used for the numerical study. The time‐varying tension of the stay cable can be identified when either a single vehicle or multiple vehicles pass over the bridge. The robustness of the proposed approach is also investigated through deviations in the initial tension, initial displacement, and velocity of the stay cable. An experiment was conducted on a scaled stay cable with time‐varying tension excited by wind. The time‐varying cable tension of the cable was identified by the proposed approach and compared with the real time‐varying cable tension. The identification accuracy and robustness of the proposed approach is verified through the experiment and numerical study. Copyright © 2013 John Wiley & Sons, Ltd.
Real‐time identification of time‐varying tension in stay cables by monitoring cable transversal acceleration
Li, Hui (author) / Zhang, Fujian (author) / Jin, Yizhou (author)
Structural Control and Health Monitoring ; 21 ; 1100-1117
2014-07-01
18 pages
Article (Journal)
Electronic Resource
English
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