Fault Diagnosis Based on Rough Set and Fuzzy Neural Network
Sun Ying-feng · Journal of Naval Aeronautical and Astronautical University · 2010
Neural network has extensively applied to fault diagnosis.By being combined with other technologies,it will achieve more superiority over its defect in redundancy of data and network construct.Rough set theory has the advantage of data reduction and rule extraction,and can initialize the structure of network.The tolerances to data of fuzzy neural network can improve the application of rough set theory;and it also provides a clear reasoning.By combining those advantages of the two technologies,the model of fault diagnosis was constructed,and the results of the simulation for fighter plane control surface fault diagnosis revealed the efficiency and practicality of this method.