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| Identification of moving vehicular parameters based on Improved Glowworm Swarm Optimization algorithm |
| Received:September 06, 2015 Revised:March 25, 2016 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx201701015 |
| KeyWord:Glowworm Swarm Optimization algorithm bridge-vehicle system moving vehicle acceleration response parameter identification |
| Author | Institution |
| 李海龙 |
中山大学 力学系, 广州 |
| 吕中荣 |
中山大学 力学系, 广州 |
| 刘济科 |
中山大学 力学系, 广州 |
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| Abstract: |
| This paper presents an indirect method for the identification of parameters of moving vehicles based on Glowworm Swarm Optimization (GSO) algorithm.Each moving vehicle is modelled as a four-degree-of-freedom system with twelve parameters.The equation of the bridge-vehicle system is established by finite element method.And Newmark direct integration method is used to calculate the dynamic response of the system.A local search method and eliminated system at last one are brought in the movement phase of GSO to enhance the accuracy and convergence rate of the algorithm.Acceleration measurements at selected stations on the vehicle are used to identify the parameters of the moving vehicle with the IGSO algorithm.Several test cases are studied to verify the efficiency of the method and the results show that the proposed method is not sensitive to measurement noise. |