摘要
文章针对车用交流发电机的特点,建立了故障现象与故障征兆列表,并应用基于模糊神经网络的故障诊断方法,实现了对该类发电机故障的模糊诊断。文中还介绍了模糊神经网络的结构和对应的学习方法,以及基于CAN总线的实时的车用交流发电机故障诊断系统的组成,该系统利用计算机作平台。仿真和试验结果表明,该诊断方法是行之有效的。
The fault phenomena and fault symptom list are established in allusion to the characteristics of vehicle alternator, and a fault diagnosis approach based on a fuzzy neural network is also applied for this alternator fault diagnosis. In this paper, the structure of the fuzzy neural network and corresponding learning method are introduced, and the structure of this real-time vehicle alternator抯 fault diagnosis system is introduced based on CAN bus and computer platform. At last, this fuzzy neural networks fault diagnosis is simulated with Matlab抯 Neural Networks Toolbox. The simulation results show the validity and practicability of this fault diagnosis system.
出处
《系统仿真学报》
CAS
CSCD
2004年第5期1001-1004,1008,共5页
Journal of System Simulation
基金
国家自然科学基金资助(50077005)
