The Development Of Fault Diagnosis Systems Of Sodium Pump For China Experiment Fast Reactor

The serious influences may be caused by equipment fault in a nuclear power station to operation safety. Hence, fault diagnosis technologies are met with altitudinal recognition in nuclear field. Along with fault diagnosis technologies used and developed, advanced fault diagnosis systems based on checking, identification, pre-measuring and intervention are applied widely and deeply in nuclear industry, which is capable of diagnosis to fault in time and truly. At the same time corresponding countermeasures adopted ensure and enhance operation safety and reliability in a nuclear power station.Based on adequate survey to faults of sodium pump for The China Experiment Fast Reactor, in order that the advanced diagnosis methods are used in the sodium pump which is under fabrication, different methods of fault diagnosis system of sodium pump are designed and programmed; and the principal component analysis (PCA)is used to fault diagnosis system of main coolant pump in a nuclear power station. The feasibility of fault diagnosis systems developed have been proved by simulation results.The main works of this thesis include:1. The wavelet packet analysis applied in fault diagnosis system is studied in this thesis. Using simulation fault data, uncalm and time difference vibration signal of sodium pump are decomposed on different levels and frequencies. To picked-up the eigenvectors reflecting different fault of sodium pump with availability, simulation results have shown its satisfaction in the identification.2, Fault diagnosis software which combines wavelet packet and expert system is developed, based on wavelet packet analysis and reverse reasoning of fault diagnosis expert system, it has diagnosis and exploration. In this way it. combines fast diagnosis ability of wavelet packet analysis with exploration ability of expert system with a sufficient, exertion of both advantages,increasing rapidity and veracity of fault diagnosis.3. A self-adapting fault diagnosis method based on radial basis function (RBF) networks is studied in the thesis. Based on the basic RBF networks, adaptive RBF networks is improved, it brings to increase precision greatly. The method is applied to sodium pump, Simulation results have shown'the better capability for detecting faults.4. High dimension was changed into low dimension by using principal component analysis method, process detecting could be carried out in the low dimension space. Squared Prediction Error(SPE) of model is detected continuously, in case abnormity is found, currently data direction is calculated by PCA method, and compared with fault character direction storeroom, thereby fault is diagnosed. This method is used in a nuclear power station, diagnosis results is better ideality, and it has been shown that it is feasible for fault diagnosis of nuclear power station and Fast Reactor sodium pump.