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建立了润滑油摩擦特性影响规律的 BP神经网络模型 ,该网络具有两路输入 ,两个神经隐层 ,可较准确地计算磨损自补偿状态下润滑油粘度和添加剂含量对 45钢 /铜摩擦副摩擦系数的影响规律 ,为摩擦学设计的程序化计算和分析提供方便且有效的工具 .
A model of BP neural network influencing the frictional characteristics of lubricating oil has been set up. The network has two inputs and two hidden layers of nerves, which can accurately calculate the viscosity and additive content of lubricating oil under the state of self-compensation. The influence law of friction coefficient provides a convenient and effective tool for procedural calculation and analysis of tribological design.