Advances in model-based fault diagnosis with evolutionary algorithms and neural networks - Witczak, Marcin (Zielona Góra: Uniwersytet Zielonogórski)
Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, the classical analyticaltechniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniquessuch as evolutionary algorithms and neural networks become more and more popular in industrial applications of faultdiagnosis. The main objective of this paper is to present recent developments regarding the application of evolutionaryalgorithms and neural networks to fault diagnosis.
Keywords: fault diagnosis; evolutionary algorithms; neural networks; robustness