A method for extracting bridge influence lines based on self-adaptive fitting
Bridge influence lines (ILs) are widely used in dynamic weighing,structure assessment,and damage identification. Extracting accurate bridge ILs from measured bridge responses is an essential issue. This paper proposed a self-adaption fitting algorithm for extracting accurate bridge ILs from bridge response. This method analyzed the mechanism of the multi-axle vehicle crossing the bridge and obtains the initial IL by matrix calculation. Then,a self-adaption fitting algorithm was used to eliminate the fluctuating disturbance in the initial IL and extract high accuracy and quasi-static bridge ILs. Static and moving load tests of the model bridge were carried out. The ILs measured from the static test were compared with the ILs extracted from the moving load tests to verify the feasibility of the proposed method. Finally,the performance of the algorithms was discussed in depth by comparing them with the existing IL extraction methods. The advantages of the proposed method were verified in terms of fluctuation,accuracy,and computational speed. The results show that the method can better extract quasi-static bridge ILs from the bridge response containing static and fluctuating components. The self-adaptive fitting method can automatically select suitable data segments for fitting according to the fluctuation of the original response. By adjusting the parameter λ,it achieves a smoothing effect while preserving data details. Moreover,this method not only has certain advantages over the existing methods in terms of accuracy,but also can achieve high accuracy after 2～3 iterations with high speed. The results can provide a novel method for bridge IL extraction,which lays the foundation for its application.
万方数据
维普
