In order to reduce turnout rail wear, the paper establishes a coupled dynamics model and a turnout rail wear model that consider the true profile of the turnout rail, the vehicle's continuous traction force while passing, and the operational resistance. Comparative analysis of various models for predicting turnout rail wear indicates that the wear energy model is better suited for this purpose. The ideal profile update step for the turnout rail is 0.05 mm, and the adaptive filtering algorithm, tailored to the turnout characteristics, smooths wear distribution effectively while retaining crucial data features. The wear model developed in the paper predicts wear depth that is 89.91% consistent with the measured data. The grinding model introduced in the paper significantly enhances the wheel-rail contact conditions in the turnout, with lateral and vertical vibration accelerations of the vehicle reduced by 52.56% and 30.43%, respectively, during turnout passage. The research offers theoretical support for mitigating rail wear in high-speed turnouts.
Keywords: High-speed turnouts; Turnout grinding; Vehicle-turnout coupled dynamic model; Wear prediction; Wheel-rail interaction.
© 2024. The Author(s).