Fault Diagnosis of Analog Circuits Based on CFNN

Mei Rong Liu,Yi Gang He,Xiang Xin Li

doi:10.4028/www.scientific.net/aef.6-7.1045

Abstract

An analog circuits fault diagnosis method based on chaotic fuzzy neural network (CFNN) is presented. The method uses the advantage of the global movement characteristic inherent in chaos to overcome the shortcomings that BPNN is usually trapped to a local optimum and it has a low speed of convergence weights. The chaotic mapping was added into BPNN algorithm, and the initial value of the network was selected. The algorithm can effectively and reliably be used in analog circuit fault diagnosis by comparing the two methods and analyzing the results of the example.

Highlights

From the 1960’s, lots of approaches and theories are presented in analog circuit fault diagnosis [1,2,3,4,5]
The fuzzy neural network (FNN) is a kind of new neural network; it is the neural network that the fuzzy method or the fuzzy weight coefficient is leaded into the network
A new method of analog circuit fault diagnosis based on chaotic fuzzy neural network (CFNN) is proposed in this paper

Summary

Introduction

From the 1960’s, lots of approaches and theories are presented in analog circuit fault diagnosis [1,2,3,4,5]. There are many difficulties in analog circuit fault diagnosis because of its continuous input and output response, the tolerance of the electric element and the non-linearity that commonly existed in analog circuit. The artificial neural network (ANN) has many virtues, such as association memory ability, strong robustness and non-linearity. It is applied widely in various fields. The fuzzy logic has the abstract thinking emulational characteristic of human brain, and the neural network has image thinking of human brain It is an important form for realization of the intelligence diagnosis that the fuzzy logic and the neural network are combined to imitate human brain in terms of both the abstract thinking and the image thinking. Compared with the ordinary neural network, the rate of accuracy in analog circuit fault diagnosis can be further enhanced when the tolerance is included; the diagnosis time has been further reduced

Fuzzy neural network

Bj j

Fuzzy neural network based on chaos theory

Findings

Conclusions