Model Updating of a Freight Wagon Based on Dynamic Tests under Different Loading Scenarios

Abstract

This article presents an efficient methodology for the calibration of a numerical model of a Sgnss freight railway wagon based on experimental modal parameters, namely natural frequencies and mode shapes. Dynamic tests were performed for two distinct static loading configurations, tare weight and current operational overload, under demanding test conditions, particularly during an unloading operation of the train and without disturbing its tight operational schedule. These conditions impose restrictions to the tests, especially regarding the test duration, sensor positioning and system excitation. The experimental setups involve the use of several high-sensitivity accelerometers strategically distributed along with the vehicle platform and bogies in the vertical direction. The modal identification was performed with the application of the enhanced frequency-domain decomposition (EFDD) method, allowing the estimation of 10 natural frequencies and mode shapes associated with structural movements of the wagon platform, which in some cases are coupled with rigid body movements. A detailed 3D FE model of the freight wagon was developed including the platform, bogies, wheelsets, primary suspensions and wheel–rail interface. The model calibration was performed sequentially, first with the unloaded wagon model and then with the loaded wagon model, resorting to an iterative method based on a genetic algorithm. The calibration process allowed the obtainment of the optimal values of eight numerical parameters, including a double estimation of the vertical stiffness of the primary suspensions under the unloaded and loaded static configurations. The results demonstrate that the primary suspensions present an elastic/almost elastic behaviour. The comparison of experimental and numerical responses before and after calibration revealed significant improvements in the numerical models and a very good correlation between the experimental and numerical responses after calibration.

Keywords

• freight wagon
• FE model
• dynamic tests
• model updating
• genetic algorithm