Sharif Digital Repository

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...