摘要
蒸汽发生器是连接核电厂一、二回路重要的换热设备,其水位的高低直接影响出口蒸汽的品质和整个核电厂的安全,因而以蒸汽发生器水位控制系统为对象,实现水位异常波动的实时在线诊断十分必要。利用MATLAB/Simulink软件构建蒸汽发生器水位控制系统并添加传感器故障模块,得到各类故障下水位和给水流量的变化特征。建立以BP神经网络为核心的故障诊断系统,实现监测数据的实时采样、在线处理和故障诊断。仿真结果表明,建立的蒸汽发生器水位控制系统在线故障诊断模型能够及时准确地诊断出故障的类型和程度,取得了预期的效果。
A steam generator is an important heat exchanger connecting the primary and secondary circuit of a nuclear power plant,and its water level directly affects the quality of outlet steam and the safety of the nuclear power plant. Therefore,it is necessary to realize the fault diagnosis of water level abnormal fluctuation in the steam generator water level control system. At first,the steam generator water level control system and its sensor fault model were set up to obtain the various fault characteristics of water level and feed water flow by the software MATLAB /Simulink. Then,the fault diagnosis system based on BP neural network was developed for real-time sampling,online data processing and fault diagnosis of data being monitored. The simulation results demonstrate that the on-line fault diagnosis model of steam generator water level control system can diagnose the fault type and degree timely and accurately,obtaining expected effect.
出处
《应用科技》
CAS
2016年第5期75-81,共7页
Applied Science and Technology
基金
国家自然科学基金项目(51379046)