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Bridge Damage Localization Using Axle Weight Time History Data Obtained through a Bridge Weigh-in-Motion System
With an increase in bridge service time, damage will inevitably occur. Accurately identifying damage is of great significance to the operation and maintenance of a bridge. To realize a frequent identification of local stiffness reduction caused by structural damage in operation, this paper proposes a new method for damage localization of short-span bridges based on the axle weight time history identified by bridge weigh-in-motion technology. This method is based on a least squares QR decomposition recursive algorithm, and the orthogonal matrix is updated by the newly added measured rotation response and the axle weight identified in the previous step to recursively obtain the current axle weight. Then, the axle weight time history is obtained and the damage is located according to the mutation of axle weight time history caused by the first axle passing through the damage. The accuracy and applicability of the proposed method are verified by a numerical model of a simply supported beam. The results show that the axle weight time history has a strong sensitivity to damage, and the average normalized axle weight time history can accurately locate the damage and significantly reduce the impact of environmental noise. This method can be used for long-term health monitoring of bridge structures.
Bridge Damage Localization Using Axle Weight Time History Data Obtained through a Bridge Weigh-in-Motion System
With an increase in bridge service time, damage will inevitably occur. Accurately identifying damage is of great significance to the operation and maintenance of a bridge. To realize a frequent identification of local stiffness reduction caused by structural damage in operation, this paper proposes a new method for damage localization of short-span bridges based on the axle weight time history identified by bridge weigh-in-motion technology. This method is based on a least squares QR decomposition recursive algorithm, and the orthogonal matrix is updated by the newly added measured rotation response and the axle weight identified in the previous step to recursively obtain the current axle weight. Then, the axle weight time history is obtained and the damage is located according to the mutation of axle weight time history caused by the first axle passing through the damage. The accuracy and applicability of the proposed method are verified by a numerical model of a simply supported beam. The results show that the axle weight time history has a strong sensitivity to damage, and the average normalized axle weight time history can accurately locate the damage and significantly reduce the impact of environmental noise. This method can be used for long-term health monitoring of bridge structures.
Bridge Damage Localization Using Axle Weight Time History Data Obtained through a Bridge Weigh-in-Motion System
Wei, Yun-Tao (Autor:in) / Yi, Ting-Hua (Autor:in) / Yang, Dong-Hui (Autor:in) / Li, Hong-Nan (Autor:in)
05.08.2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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