A neural network-based approach for fault diagnosis in non-linear analog systems

Abstract

A new interesting technique for fault diagnosis in non-linear analog systems is presented. The approach is based on a neural network interpolator for the construction of a fault dictionary in the frequency domain. A multi-layered architecture with one hidden layer is chosen in order to locate and to identify the most likely faulty element of the System Under Test (SUT).<>