摘要
用单一理论和方法对复杂系统进行故障诊断效果不太好.文章讨论了基于神经网络和模糊系统的故障诊断以及它们之间结合方式的特点,提出了一种保障工业生产安全可靠运行的有效方法:分级故障诊断算法+过程监控与报警,仿真并设计了基于工控网络的工业过程故障诊断与报警系统.研究表明基于径向基函数神经网络+模糊逻辑的算法具有较快的训练速度和较好的泛化能力,可识别多回路故障.
Fault diagnosis to complex system with one method is insufficient. The characteristics of fault diagnosis based on neural networks and fuzzy logic systems and their union wers discussed. A kind of effective method to safeguard industrial production was presented： graduation fault diagnosis and alarm system. Fault diagnosis and alarm system based on industrial control nets were simulated and designed. The results show that the algorithm based on radial basis function neural network and fuzzy logic has faster training speed and better generalization ability, and it can distinguish multi-routes faults.
出处
《动力学与控制学报》
2006年第3期284-288,共5页
Journal of Dynamics and Control
关键词
故障诊断
神经网络
模糊逻辑
工业过程
fault diagnosis, neural network, fuzzy logic inference, industrial process
