Application de nouvelles techniques de traitement de signal pour la résolution des problèmes de diagnostiques de défauts des circuits analogiques intégrés

Abstract

his present work aims to contribute to the solution of the problems encountered in electronic circuits fault diagnosis. One of these troubleshoots faced is the lack of effective features that help to optimize fault classifier and hence improve circuit fault detection and identification. Thus, our feature extraction approach is based on the CUT's transfer function. In order to detect and identified those faults, we used several techniques from treatment of signal, such us Matlab identification system IS model (ISM), namely the OE model belonging to the ARMA model’s family.These features are the transfer function polynomial coefficients playing a crucial role in the fault free and faulty circuits construction models and feeding the classifier for the fault diagnosis purpose. A best accuracy and a best reduction for coefficients are obtained by using of an algorithms combination GA-SVM.