Application of radial basis function network to the preventive maintenance of electronic analog circuits

The ability to detect soft fault is an important task in the preventive maintenance. In this paper a neural network based approach to fault detection of both linear and non linear circuits is presented. In particular Radial Basis Functions (RBF) networks are used to analyse circuit input-output measurements, and to localise faulty element. These methods exploit the capabilities, typical of neural networks, to analyze and classify signatures acid to deal with problems involving poorly defined system models, noisy input environment and non-linear behaviors