摘要
以RBF网络为识别模型,对柴油机燃油喷射系统的故障进行训练,并应用于待识别故障样本的识别仿真,结果表明,基于RBF的故障诊断方法优于基于BP网络故障诊断,在柴油机燃油喷射系统故障诊断中是行之有效的方法。
The Radial Basis Function neural network with some fault samples of fuel injection system is trained and the neural network model is applied to identify the samples to be identified. The result indicates that the method is better than the fault diagnosis based on BP neural network and efficiency in the fault diagnosis of fuel injection system.
出处
《机械制造与自动化》
2007年第2期74-75,84,共3页
Machine Building & Automation
关键词
径向基函数
故障诊断
柱塞磨损
神经网络
RBF （radial basis function）
fault diagnosis
fuel injection system
neural network
