Fault Testing and Diagnosis in Analog Circuits Using Fault Dictionary Techniques

Abstract

The present study aims to test and diagnose fault in analog-based equipment including biological and medical laboratory equipment. The diagnosis has been performed using fault dictionary techniques by modern classification methods. The modern classification methods include probabilistic neural networks and wavelets. It is known that analog circuits have difficulties compared to the digital circuits due to lack of efficient fault modeling, tolerance, nonlinearity, parametric effects and other effects. In this study, the fault diagnosis by simulation before-test approach in order to obtain a very high diagnostic degree was performed.