摘要
径向基函数 (RBF)神经网络是一种 3层前馈性神经网络 ,它具有较强的函数逼近能力和分类能力。鉴于径向基函数神经网络的优点 ,在对滚动轴承振动信号特征分析的基础上 ,提出了采用时序方法对其建立AR模型 ,利用AR模型参数建立径向基函数神经网络 ,并用该网络对滚动轴承的故障模式进行了识别。理论和试验证明了该方法的有效性 。
Radial basis function neural network is a type of three-layer feedforward network. It has many good properties, such as powerful ability for function approximation, classification and learning rapidly. In this paper, in the light of the merit of radial basis function neural network and on the basis of the feature analysis of vibration signal of rolling bearing, AR model is presented by using time series method. Radial basis function neural networks is established based on AR model parameters. In the light of the theory of radial basis function neural networks, fault pattern of rolling bearing is recognized correspondingly. Theory and experiment show that the recognition of fault pattern of rolling bearing based on radial basis function neural networks theory is available and its precision is high.
出处
《中国工程科学》
2004年第2期56-60,共5页
Strategic Study of CAE
基金
吉林省教育委员会基金资助项目 (吉教合字 99第 10号 )
