Monitoring and fault diagnosis of the steam generator system of a nuclear power plant using data-driven modeling and residual space analysis
Monitoring and fault diagnosis of the steam generator system of a nuclear power plant using data-driven modeling and residual space analysis
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DOI：
10.1016/j.anucene.2005.02.003
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发表时间：
2005-06-01
影响因子：
1.9
通讯作者：
Upadhyaya, BR
中科院分区：
文献类型：
--
作者：
Lu, B;Upadhyaya, BR
针对典型压水堆核电站蒸汽发生器系统，提出了一种先进的故障检测与隔离（FDI）技术。系统表征模块采用数据处理方法中的成组方法，对U型管蒸汽发生器（UTSG）的各种过程变量之间的相互关系进行建模。利用主成分分析算法生成具有代表性的故障特征。故障识别的准确性量化使用归一化向量投影到故障空间。其他经典的模式分类方法并行执行，以增加FDI结果的鲁棒性。通过对一台四回路压水堆的全范围仿真，成功地检测和隔离了六种典型的静态故障和一种瞬态故障。结果表明，仪器和执行器监测的FDI算法的实施。(c)2005爱思唯尔有限公司保留所有权利。
An advanced fault detection and isolation (FDI) technique was developed for the steam generator system of a typical pressurized water reactor (PWR) plant. The system characterization module used the group method of data handling method for modeling the interrelationship among the various process variables associated with a U-tube steam generator (UTSG). A principal component analysis algorithm was utilized for the generation of representative fault signatures. The accuracy of fault identification was quantified using normalized vector projections on to fault spaces. Other classical pattern classification methods were executed in parallel to increase the robustness of FDI results. Six typical static faults and one transient fault were successfully detected and isolated using a full-scope simulation of a four-loop PWR. The results demonstrate the implementation of the FDI algorithm for both instrument and actuator monitoring. (c) 2005 Elsevier Ltd. All rights reserved.