基于模糊BP神经网络的模拟电路实时故障诊断

Analogue circuit real-time faults diagnosis based on fuzzy BP neural network

以进行模拟电路实时故障诊断为主要目的,对BP神经网络故障字典法进行了深入研究,针对传统BP算法收敛速度慢、易产生局部最优等不足,采用神经网络与模糊理论相结合的方法,根据模式识别原理实现模拟电路故障的实时诊断。实验结果表明:该算法在网络收敛速度和识别精度上较传统的BP算法均有明显的改善。

The main purpose is to realize the real time fault diagnosis of analog circuit. The BP neural network fault dictionary is deeply researched on. Aimed at the deficiency of BP algorithm and based on the theory of mode identification, the fault diagnosis of analogy circuit is realized by neural network combined with fuzzy theory. The experiment result shows that the improved BP algorithm has distinct improvements on convergent velocity and identification precision.