Application research of intelligent fault diagnosis technology in the nuclear power plant
Chun-li Xie · Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University · 2007
The security performance requirement is higher for the system in nuclear power plants.In order to let the operator avoid wrong judgment and operation when fault happens,one better method is to apply the intelligent fault diagnosis technology in the fault diagnosis system of nuclear power plant.Using the reduction technology of rough set(RS) method to draw a simple rule from a large number of initial data,the fuzzy neural network(FNN) set up on the basis of these rules has better topological structure,the speed of study is improved,and the fault-tolerant ability is strong.The radial basis function(RBF) network has very good partial performance,the ability of diagnosis for single fault has surpassed the FNN.The network doesn't need the training,and the diagnosis has good real-time character.The combination of FNN based on RS theory and RBF neural networks can take full advantage of one's own.In order to test the validity of the method,the inverted U-tubes break accident of steam generator,etc.were used as examples and many simulation experiments were performed.The result of study indicates that confederate network has good diagnosis accuracy,real-time character and expandability,and has obtained the anticipated effect.