MATLAB神经网络列车智能诊断系统设计+源程序
毕业论文关键词：列车；故障诊断；RBF神经网络；MATLAB；
Train intelligent diagnostic system design based on neural network
Abstract：The main article in the high-speed train running, how fast and accurate fault monitoring equipment on the train tiny, tiny malfunction can cause major accidents. After learning the diagnostic technique trains, as well as its domestic and international development, , its diagnosis through the neural network of the method. Neural networks are also many types such as: RBF neural network and BP neural network. Since contrast functional RBF neural network and BP neural network RBF neural network has drawn good adaptability, self-organization and strong ability to learn effectively determine the network structure model, we decided to use the RBF neural network. In order to achieve more intuitive and easy to train intelligent diagnosis based on RBF using MATLAB software design an intelligent diagnostic system train axle rotor fault detection. then training with RBF neural network diagnostic results Train Axle rotor fault type. Finally, implementation of the system for train axle rotor types of faults: Diagnostic rotor misalignment, rotor cracks, oil whirl.
Key Words: Train; Fault diagnosis；RBF neural network；MATLAB；
目 录
1 绪论 1
1.1 课题的目的及意义 1
1.2 国内外研究概况 2
1.2.1 国内研究概况 2
1.2.2 国外研究概况 3
1.3 本文的主要内容 4
2 列车关键部件常见故障 5
2.1 列车关键部件故障诊断 5
2.1.1 简介 5
2.1.2 分类 5
2.2 列车关键部位常见故障 6
2.3 故障常见研究方法 7
2.4 本章小结 8
3 RBF神经网络 9
3.1 RBF神经网络介绍 9
3.1.1 RBF神经网络的拓扑结构 9
3.1.2 RBF网络中的几种调用函数 9
3.2 RBF与BP的对比 10
3.3 RBF神经网络的训练 11
3.4 本章小结 12
4 诊断系统的设计、实现与验证 13
4.1 系统设计 13
4.1.1 使用软件简介 13
4.1.2 系统设计原理 13
4.1.3 建立系统界面 14
4.2 系统实现 18
4.3 系统验证 18
4.3.1 以FFT分析为特征提取的工具 18
4.3.2 转子故障诊断系统的演示 20
4.4 本章小结 21
5 结论与展望 22