Research for Fault Diagnosis of Aeroengine Based on Fuzzy Neural Network

In the aero engine fault diagnosis, taking consideration into the complex non-linear relationship between faults and symptoms, this paper proposes a new intelligent fault diagnosis based on fuzzy neural network. The diagnosis theory and the arithmetic of the method are described in detail. And the model of aero engine failure is set up by using measured data at vibration faults as learning samples. The experimental results demonstrate that, compared with the traditional methods such as BP neural network and fuzzy logic, the fuzzy neural network proposed can not only effectively improve the accuracy of fault diagnosis, but also evaluate the possibility and severity of various of faults, which make the diagnosis results more practical.