基于模糊系统与神经网络融合的故障诊断方法  

A Fault Diagnosis Approach Based on Neural Network Driven Fuzzy System

作　　者：孙勤刚[1] 刘登第[2] 谢华[3] 

机构地区：[1]武汉钢铁公司炼铁厂 [2]武汉钢铁公司炼铁厂 [3]空军第一航空学院

出　　处：《中国安全科学学报》1999年第2期37-41,共5页China Safety Science Journal

摘　　要：提出一种基于模糊系统（ＦＳ）与神经网络（ＮＮ）融合的系统故障诊断方法。此法把模糊系统与神经网络融合在一起，通过神经网络的学习来生成和调整模糊系统的隶属函数，充分发挥各自优点，更有效地对系统出现的故障进行诊断。对系统进行了仿真，并得出了比较满意的结果。A fault diagnosis approach based on neural network driven fuzzy system is presented, which combines the fuzzy logic with neural network to demonstrate fully their own disadvantages and advantages and to diagnose more effectively the fault appeared in the system. This approach takes the advantage of the learning ability of the neural networks to regulate functions of the fuzzy system. The system is simulated with satisfactory result.

关 键 词：模糊系统 神经网络 故障诊断 数据融合 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]