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fermentation-bioreactor
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Fault Detection in Plant Wide
,
Ph.D. Dissertation
Sharif University of Technology
;
Bozorgmehry, Ramin
(Supervisor)
;
Shahrokhi, Mohammad
(Supervisor)
Abstract
The accurate fault diagnosing system design helps the process safety and also helps increasing the products quality of the process. In this project, the fuzzy system and neural network have been used for fault detection and diagnosis of a yeast fermentation bioreactor. In one case, parameters of membership functions are selected in a conventional manner. In second case, the optimal values of these parameters have been obtained using the genetic algorithm. In another case, the neural network system is used for fault detection. These three cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The results indicate...
Fault diagnosis in a yeast fermentation bioreactor by genetic fuzzy system
, Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 29, Issue 3 , 2010 , Pages 61-72 ; 10219986 (ISSN) ; Shahrokhi, M ; Bozorgmehry Boozarjomehry, R ; Sharif University of Technology
Abstract
In this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. In one case, parameters of membership functions are selected in a conventional manner. In another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genetic algorithm. These two cases are compared based on their performances in fault diagnosis of a yeast fermentation bioreactor for three different conditions. The simulation results indicate that the fuzzy-genetic system is superior in multiple fault detection for the conditions where the minimum and...