Multiple Linear Regression Method for Deeper Analyses of Abrasive Tribological Behaviour of Engineering Materials

G. Kalácska
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Abstract

Tribology (friction, wear, lubrication) studies the elements made of different materials in relative motion. While the individual materials can be well characterized e.g. by their physical and chemical properties the description and prediction of the friction and wear behaviour is not an easy task. There is no uniform, analytical calculation method, because the behaviour of the structural materials depends on the operating conditions and the effects occurring during operation, thus, the tribological behaviour is system dependent. In order to have information about wear, friction and heat generation during operation, it is advisable to use the modelling method. The result of either mechanical or numerical modelling can help machine designers. The use of simplified models performed under laboratory conditions (DIN50322, testing category VI.) is very common, where relative comparison of friction materials is possible under fixed conditions. The laboratory tribotest equipments are usually suitable for online data collection, so that friction force, heat generation, wear and deformation can be continuously recorded during a sliding process. These datasets provide an opportunity not only for primary trend analysis of the measured quantities, but also for in-depth analysis of the relationships between tribological trends and material characteristics. Hundreds of articles have been published in the tribological literature where wear, surface deformation, or friction have been evaluated as a function of some material characteristics or simple combinations thereof. The first famous results e.g. in the field of abrasion wear, the wear estimates published by Lancaster in the late 1960s [1]. Not highlighting each work, overall the surface hardness (H), tensile modulus of elasticity (E) and tensile strength (R) were mainly in focus, as a function of which tribological processes, the friction and wear behaviour of materials were evaluated.
工程材料磨料摩擦学性能深入分析的多元线性回归方法
摩擦学(摩擦、磨损、润滑)研究由不同材料组成的元件在相对运动中的情况。虽然单个材料可以很好地表征,例如通过它们的物理和化学性质,但描述和预测摩擦和磨损行为并不是一件容易的事。没有统一的分析计算方法,因为结构材料的行为取决于操作条件和操作过程中发生的影响,因此,摩擦学行为依赖于系统。为了获得运行过程中有关磨损、摩擦和热量产生的信息,建议使用建模方法。机械或数值建模的结果可以帮助机器设计者。使用在实验室条件下进行的简化模型(DIN50322,测试类别VI.)是非常常见的,在固定条件下可以对摩擦材料进行相对比较。实验室摩擦测试设备通常适合在线采集数据,以便在滑动过程中连续记录摩擦力,热量产生,磨损和变形。这些数据集不仅为测量量的主要趋势分析提供了机会,而且还为深入分析摩擦学趋势与材料特性之间的关系提供了机会。摩擦学文献中已经发表了数百篇文章,其中磨损,表面变形或摩擦已被评估为某些材料特性的函数或其简单组合。第一个著名的结果是在磨损领域,由兰开斯特在20世纪60年代末发表的磨损估计[1]。没有突出每项工作,总体而言,表面硬度(H),拉伸弹性模量(E)和拉伸强度(R)是重点,作为摩擦学过程的函数,材料的摩擦和磨损行为被评估。
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