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以AA6061为基体、AlN颗粒为增强体,采用搅拌铸造工艺得到AA6061-T6/AlNp复合材料,研究了AA6061-T6/AlNp复合材料的干滑动磨损行为。开发回归模型来预测复合材料的磨损率。采用四因素、五水平的正交实验进行优化。实验因素包括滑动速度、滑动距离、荷载、增强体AlN颗粒的质量分数。采用SYSTAT 12软件和统计工具,如方差分析(方差分析)和t实验,验证回归模型。结果表明,开发的回归模型可以有效预测复合材料的磨损率,置信度达95%。采用回归模型,并依据磨损表面形貌分析,预测实验因素对AA6061-T6/AlNp复合材料磨损率的影响。回归模型预测结果表明,复合材料的磨损率随着增强体AlN质量分数的增加而降低,随着滑动速度、滑动距离、荷载的增加而增加。
Using AA6061 as matrix and AlN particles as reinforcement, the AA6061-T6 / AlNp composite was obtained by a stirring casting process. The dry sliding wear behavior of AA6061-T6 / AlNp composites was investigated. Develop a regression model to predict the wear rate of the composite. Using four factors, five levels of orthogonal experiments to optimize. Experimental factors include the sliding speed, sliding distance, load, mass fraction of reinforced AlN particles. The regression model was validated using SYSTAT 12 software and statistical tools such as analysis of variance (ANOVA) and t-experiments. The results show that the developed regression model can effectively predict the wear rate of composite materials, with a confidence level of 95%. The regression model was used and the effect of experimental factors on the wear rate of AA6061-T6 / AlNp composites was predicted based on the analysis of wear surface morphology. The regression model predicts that the wear rate of the composites decreases with the increase of AlN mass fraction, and increases with the sliding speed, sliding distance and load.