基于多次回归分析的高钒高速钢滚动磨损模型

Rolling wear model of high-vanadium high-speed steel based on multiple regression analysis

利用自制的滚动磨损试验机，测试了4种高钒高速钢的磨损性能，利用回归方法建立了磨损量关于循环次数和基体中碳含量的二元方程模型。结果表明：该模型可较准确地预测高速钢的磨损性能；预测结果揭示，基体中碳含量为0．48％～0．50％时，基体组织主要为低碳板条马氏体，硬度高且韧性较好，可以同时有效的抵御显微切削及疲劳磨损，磨损性能最佳。当基体中碳含量过低时，基体中出现大量硬度很低的铁素体相，显微切削为高速钢的主要磨损机制，而碳含量过高时，基体主要为韧性差的高碳马氏体，高速钢以疲劳磨损为主，二者均导致耐磨性下降。

The wear properties of four kinds of high-vanadium high-speed steel with different carbon content were tested on a self-made rolling wear machine. By use of multiple regression analysis, a model of wear weight loss vs number of revolutions and carbon content in matrix is based on the experimental data. The test results show that the model can be used to predict wear properties of high speed steel. The prediction results indicate that the matrix microstructure of high speed steel is mainly low carbon lath martensite with good toughness and high hardness when carbon content in matrix is about 0.48% - 0.50%, resulting in the optimal wear property of roll. If carbon content in the matrix is very low, the wear failure of high-speed steel is mainly caused by severe micro-cutting because much ferrite with very low hardness is formed in matrix, leading to the decreasing of wear resistance. However, the matrix microstructure mainly consists of high carbon martensite with poor toughness for the matrix with very high, and therefore the high speed steel is easy to wear fatigue, resulting in poor wear property.