Web-based Chinese Experimental Fast Reactor Research And Development Of Important Equipment Of Remote Fault Diagnosis System

Equipment failure diagnosis should be concerned in nuclear power plants because equipment failure could lead to serious problems on operation safety. With the rapid development of computer technology in recent years, the Internet is affecting and changing our life style, so Web-based failure diagnosis becomes inevitable trend in equipment failure diagnosis. In this paper, The Web-based remote monitoring and failure diagnosis system is developed for important equipments of China Experiment Fast Reactor (CEFR), while remote failure diagnosis is researched and developed. The main results are as follows:(1) Analyzing CEFR's status and designed computer monitoring system; Discussing feasibility and function & requirement of remote monitoring and failure diagnosis system for CEFR; Confirming pattern of system frame, the whole design case and used method and software.(2) Based on the overall structure of the system design, the paper gives the system flow charts and system operating principles maps by the technical achievement method. The entire system is divided into two modules: Real-time data collection module or namely the local server module; Remote online monitoring and failure diagnosis module or namely remote client server modules. The modules are respectively realized by VC＋＋6.0, Microsoft Visual Studio. NET and COM technology. Based on the B/S framework, the remote monitoring and failure diagnostic platform for important equipments in CEFR is developed. The software interface is designed in consequence to link the correlative systems and the failure diagnosis module.(3) Contraposing sodium pump (one of the important equipments in CEFR), using vibration monitoring methods, the models of failure is established by simulating the sodium pump failure on the basis of the design parameters. The paper uses the method of wavelet pack decomposition to analyse the non-smooth vibration signals effectively while choosing Daubechies wavelet as the base wavelet of the decomposition because of its characteristics.(4) The system works properly while debugging and testing the entire system on application of a collection card to collect signals from generators. Simulating the normal and abnormal signals of sodium pump operation, it is proved that the failure diagnostic method in this paper is correct and effective.