Research of Fault Diagnosis Based on Neural Networks and D-S Evidence for Condenser in Power Plant
Condenser is one of the most important auxiliaries of turbine generator unit in power plant,whose operating condition decisively affects the safe and economically operation of the whole plant.Combination the thought of information fusion,the method of condenser integrated fault diagnosis based on neural networks and D-S evidence theory is proposed.The respective diagnosis results regarded as the D-S evidence theory primary evidences in decision layer according to BP neural network and CPN network are obtained first,and then these results are fused by using of the D-S evidence theory to obtain the final diagnosis result.The diagnosis results show that this method has a smaller error and higher diagnosis reliability comparing with the results from the single neural network.
Information fusionNeural networksD-S evidence theoryFault diagnosisCondenser
NETL
NSTL
万方数据
维普
