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根据模糊数学和神经网络的基本原理 ,建立了一个基于模糊神经网络的微光电视故障诊断系统模型 ,介绍了其输入变量模糊化及其神经子网络的实现、模糊规则及其神经子网络的实现。它克服了传统域值判断在临界点附近容易误判的弊端 ,大大提高故障检测准确率 ,拓宽了故障检测范围。经过大量的实地实验 ,证明该方法是完全可行的
According to the basic principles of fuzzy mathematics and neural network, this paper establishes a microgrid fault diagnosis system model based on fuzzy neural network. It introduces the fuzzification of input variables and the realization of its neural subnetworks. The implementation of fuzzy rules and its neural subnetworks . The utility model overcomes the defects that the traditional threshold value is easily misjudged near the critical point, greatly improves the accuracy of the fault detection, and broadens the scope of the fault detection. After a large number of field experiments, this method is proved to be completely feasible