工业齿轮油承载能力与极压添加剂特性的关系

RELATIONSHIP BETWEEN CARRYING CAPACITY OF INDUSTRIAL GEAR OIL AND CHARACTERISTIC PARAMETERS OF ITS EXTREME PRESSURE ADDITIVES

探讨了利用工业齿轮油添加剂的特性预测工业齿轮油承载能力的现实性和可行性。研究结果表明，应用二次多项式模型和ＢＰ模型人工神经网络均能够有效地建立起工业齿轮油组成与性能之间的关系，特别是人工神经网络模型，能较好地预测工业齿轮油的承载能力，尽管这种关系呈现出非线性的特性。建立这种关系对润滑油的调合是十分有利的。

The feasibility of predicting carrying capacity of industrial gear oils with characteristic parameters of extreme pressure additives has been discussed. The results showed that second order polynomials and BP neural network can predict the carrying capacity with the additive's characteristic parameters, especially, BP model exhibited better prediction. Although the relation gave stronger non linear characteristics, it was still useful for formulating industrial gear oils.