International Journal of Applied Engineering Research

Fault diagnosis in analog circuits has been an active area of research for many decades. The motivation for research in this area is that analog systems are unreliable due to their poor fault models, large component tolerances and nonlinear performance. All these make application of intelligent computing techniques imperative for this area. Efforts are being made to make computer based fault diagnosis techniques better, by use of developments in the field of Artificial Intelligence. Intelligent Reasoning techniques have significantly contributed towards this end. One such popular technique is Probabilistic Reasoning. This technique allows incorporation of a priori knowledge into the diagnosis system. The probability based decision-making system for arriving at an appropriate fault decision forms the core of Probabilistic Intelligent Fault Diagnosis. The application of probabilistic decision-making for fault diagnosis in analog circuits has, therefore, become a popular area of research. The state of art in this emerging discipline has been presented in this paper.

The authors of this paper have proposed an innovative Probabilistic Technique for Intelligent Fault Diagnosis. The application of the proposed technique has been illustrated with example of fault diagnosis in Television Receiver using Visual Symptoms. Surprisingly, very little work has been reported in the literature on fault diagnosis in Television Receiver Circuits. It is expected that this paper will promote research in this nascent area.