Development of dynamic neural networks with application to observer-based fault detection and isolation - Marcu, Teodor; Mirea, Letitia; Frank, Paul M. (Zielona Góra: Uniwersytet Zielonogórski)
The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour.
Keywords: fault diagnosis; dynamic neural networks; system identification; static neural classifiers; three-tank system