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水轮机轴承非线性油膜力的径向基神经网络算法

Calculation of Nonlinear Oil-Film Force on Hydrodynamic Bearing Based on RBF Neural Network
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摘要 通过对基于免疫原理的RBF神经网络在线学习算法的改进,利用网络的非线性逼近能力,对水轮机组轴系中非线性轴承油膜力进行计算,建立了从轴承状态参数到油膜力的非线性映射关系。并通过实例验算证明,可弥补原算法中较难选择初始参数的缺陷,加上对个别计算法则作的修改,使其更符合RBF神经网络工作的物理特性,从而拓展了机组轴承油膜力的计算方法。 Based on improving immune principles online training algorithm, In this papar, we use the nonlinear approach ability of RBF network to calculate the oil-film force in Hydrodynamic bearing, thus establish a nonlinear mapping relationship from bearing status parameters to oil-film force.
出处 《江西电力》 2007年第2期12-14,49,共4页 Jiangxi Electric Power
关键词 免疫原理 RBF神经网络 水轮机轴承 油膜力 非线性 immune principle RBF neural network hydrodynamic bearing oil-film force nonlinear
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