New developments using AI in fault diagnosis
This paper is intended to give a survey on the state of the art of model-based fault diagnosis for dynamic processes employing artificial intelligence approaches. Emphasis is placed upon the use of fuzzy models for residual generation and fuzzy logic for residual evaluation. By the suggestion of a knowledge-based observer-like concept for residual generation, the basic idea of a novel observer concept, the so-called ''knowledge observer'', is introduced. The neural-network approach for residual generation and evaluation is outlined as well. (C) 1997 Elsevier Science Ltd. All rights reserved.
fault diagnosis artificial intelligence fuzzy logic neural networks knowledge-based systems qualitative simulation