Future Trends in Soft Computing Industrial Applications

2006 ◽  
Author(s):  
A.K. Kordon
Keyword(s):  
Soft Computing ◽  
Industrial Applications ◽  
Future Trends

scholarly journals Towards Robustness in Neural Network Based Fault Diagnosis

2008 ◽  
Vol 18 (4) ◽  
pp. 443-454 ◽  
Author(s):  
Krzysztof Patan ◽  
Marcin Witczak ◽  
Józef Korbicz
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fault Diagnosis ◽  
Soft Computing ◽  
Analytical Techniques ◽  
Industrial Applications ◽  
Nonlinear Behaviour ◽  
Design Problems ◽  
Modelling Uncertainty ◽  
Soft Computing Techniques

Towards Robustness in Neural Network Based Fault DiagnosisChallenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.

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