基于模糊神经网络融合遗传算法的模拟电路故障诊断法

A Method for Fault Diagnosis of Analog Circuits Using Fuzzy Neural Network Combined with Genetic Algorithms

该文提出了一种非线性模拟系统的故障辨识方法,构造了一个基于模糊加权型推理法的模糊神经网络,利用遗传算法来训练网络连接权值、优化隶属度函数,根据训练后的网络权值可以自动提取出模糊规则,并通过仿真实验验证了该方法的有效性。

A fault identification approach for nonlinear analogue systems is presented. A fuzzy neural network is developed based on the improved fuzzy weighted reasoning method. The training of network weights and the optimization of membership functions are conducted employing genetic algorithms. Fuzzy rules can be automatically obtained according to the weights of the network. The availability of the method is examined by simulated tests.