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Shock and Vibration
Volume 2016, Article ID 8249851, 13 pages
http://dx.doi.org/10.1155/2016/8249851
Research Article

Parameters Identification of Moving Load Using ANN and Dynamic Strain

1Beijing Key Laboratory of Earthquake Engineering and Structural Retrofit, Beijing University of Technology, Beijing 100124, China
2Beijing Collaborative Innovation Center for Metropolitan Transportation, Beijing 100124, China

Received 25 December 2015; Accepted 2 March 2016

Academic Editor: Rafał Burdzik

Copyright © 2016 Hui Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Moving load identification is an important part of bridge structure health monitoring; accurate and reliable load data can be used to check the load of bridge design, and the load spectrum can provide a more practical basis for structural fatigue analysis. The method of the BP neural network is used in bridge moving loads identification. The numerical examples of identification of the axle loads of a two-axle vehicle moving on a simply supported bridge under various speeds and weights are carried out. The sensitivity of the bridge deflection and strain to moving loads is analyzed, and the influences of different activation function combinations and algorithm on network are discussed. The identification results of different load conditions are analyzed and the effect of noise is considered. Finally the rationality of the method is verified by experiments. It is shown that the indirect estimation of vehicle weight by BP neural network from dynamic responses is feasible.