SVM在金属塑性成形摩擦系数预测中的应用研究

针对金属塑性成形过程中摩擦系数较难确定的客观情况，提出一种基于支持向量机的能够快速预测摩擦系数的方法。利用支持向量机建立了金属塑性成形中润滑油、模具表面粗糙度、滑动速度和金属材料表面粗糙度与摩擦系数的支持向量机模型．实验结果表明这种模型具有很好的精确度和预测性，为摩擦学设计和程序化计算和分析提供了一种方便且有效的工具。

The Implicational Research on the Prediction of Friction Coefficient in Metal Plastic Forming Process Based on SVM

Directing at the circumstance that the friction coefficient of the metal plastic forming process is difficult to confirm. A new method is proposed based on support vector machine, which can quickly predict the friction coefficient. The support vector machine is used to construct the support vector machine model of the lubricating oil in metal plastic forming process, the surface roughness of the die, the gliding rate, the surface roughness and friction of the metal materials. The experimental results show that this model has excellent accuracy and prophetical and provide a convenient and effective tool for the design of tribology and the programmable computing.