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Bridge Influence Line Identification Based on Regularized Least-Squares QR Decomposition Method
The bridge influence line is an important tool to study the bridge response under moving loads and contains tremendous structural information. Structural deterioration during the bridge’s service life will induce variation in the bridge influence line, which makes it essential to identify the influence line exactly from the field measurement data under moving vehicle loads. This article establishes the underdetermined influence line identification model for a bridge under multiaxle vehicle excitation, in which the bridge influence line is identified based on the regularized least-squares QR decomposition method. Then an example of a four-span girder bridge is provided to prove the validity of the method, and the accuracy and computational complexity of different methods in this condition are compared. This study thus provides an effective method for the identification of the bridge influence line with very high computational efficiency and identification accuracy.
Bridge Influence Line Identification Based on Regularized Least-Squares QR Decomposition Method
The bridge influence line is an important tool to study the bridge response under moving loads and contains tremendous structural information. Structural deterioration during the bridge’s service life will induce variation in the bridge influence line, which makes it essential to identify the influence line exactly from the field measurement data under moving vehicle loads. This article establishes the underdetermined influence line identification model for a bridge under multiaxle vehicle excitation, in which the bridge influence line is identified based on the regularized least-squares QR decomposition method. Then an example of a four-span girder bridge is provided to prove the validity of the method, and the accuracy and computational complexity of different methods in this condition are compared. This study thus provides an effective method for the identification of the bridge influence line with very high computational efficiency and identification accuracy.
Bridge Influence Line Identification Based on Regularized Least-Squares QR Decomposition Method
Zheng, Xu (Autor:in) / Yang, Dong-Hui (Autor:in) / Yi, Ting-Hua (Autor:in) / Li, Hong-Nan (Autor:in) / Chen, Zhi-Wei (Autor:in)
20.05.2019
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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