A semi-automatic methodology for tire’s wear evaluation

A. Castriota, M. De Giorgi, Fabio Manco, A. Morabito, R. Nobile
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Abstract

In this work, the authors aim at developing a reliable and fast methodology to evaluate the wear evolution in tire starting from a complete optical 3D scanning. Starting from a data cloud, a semi-automatic methodology was implemented in MATLAB to extract mean tread radial profiles in correspondence of the desired angular position of the tire. These profiles could be numerically evaluated to establish the presence of irregular wear and the characteristic parameter of the groove depth. The reliability and the robustness of this methodology was firstly tested by applying it to several synthetic case studies modeled in CATIA V5®, where ovalization and presence of defects were also simulated. The groove depth was determined with an error lower than 1% for the ideal model, while the introduction of ovalization and defects leaded to an error of 2.6% in the worst condition. In a second time, the methodology has been successfully applied to experimental measurements carried out in two different wear life of the tire, allowing the tracking of the wear phenomena through the evaluation of the progressive lowering of tread radial profiles.
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轮胎磨损评估的半自动方法
在这项工作中,作者旨在开发一种可靠和快速的方法来评估轮胎的磨损演变,从完整的光学3D扫描开始。从数据云中出发,在MATLAB中实现了一种半自动方法,以提取与期望轮胎角位置对应的平均胎面径向轮廓。可以对这些轮廓进行数值评估,以确定是否存在不规则磨损和凹槽深度的特征参数。该方法的可靠性和鲁棒性首先通过将其应用于CATIA V5®中建模的几个综合案例研究来测试,其中卵化和缺陷的存在也进行了模拟。在理想模型中,沟槽深度的误差小于1%,而在最坏的情况下,椭圆化和缺陷的引入导致误差为2.6%。在第二次,该方法已成功地应用于在两个不同的轮胎磨损寿命进行的实验测量,允许跟踪磨损现象通过评估逐步降低胎面径向轮廓。
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