Fault diagnosis in power plant based on multi-neural network

Due to the complexity of the power plant production environment, it brings some difficulties to troubleshooting of turbine generator. Although the approach based on neural network has been widely used in fault diagnosis of equipment, the result of fault diagnosis, which is given by the single neural network, is often not ready to determine the fault type for turbine generator. In response to this situation, a fault diagnosis method based on multi-neural network is proposed on this paper. It means that the different neural network is to be used respectively for fault diagnosis of turbine vibration firstly. Then the results of these initial diagnoses are to be integrated with information fusion technology. Through this strategy, the reliable result of fault diagnosis is obtained and the disadvantage of inaccurate diagnosis based on a single neural network is overcome.