Research and Implementation of Anomaly Detection and Fault Diagnosis System for Chemical Control in Nuclear Power Plants
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摘要: 目前核电厂主要依靠化学工程师进行化学控制异常检测与故障排查，受限于化学工程师个人经验和技能水平，造成异常检测与故障排查存在时效性差和准确性无法保证的问题。为解决此问题，设计了一套核电厂化学控制异常检测与故障诊断系统。在研究过程中重点探讨了核电厂化学控制异常数据检测规则库设计、故障诊断库设计以及异常检测与故障诊断等关键技术。通过在某核电厂的实际应用证明该系统能有效地自动检测化学监测数据异常并进行故障诊断。这一研究成果可显著提升核电厂的化学控制水平，为核电厂安全运行提供保障。Abstract: At present, nuclear power plants mainly rely on chemical engineers for the anomaly detection and troubleshooting of chemical control, which is limited by the personal experience and skill level of chemical engineers, resulting in the problems of poor timeliness and inaccuracy in anomaly detection and troubleshooting. To address this issue, a set of anomaly detection and fault diagnosis system for chemical control in nuclear power plant is designed and implemented. During the research process, we focused on exploring key technologies such as anomaly detection rule databse, fault diagnosis database, and anomaly detection and fault diagnosis. Through the practical application in a nuclear power plant, it is proved that the system can effectively and automatically detect abnormalities in chemical monitoring data and diagnose abnormal faults, thereby improving the chemical control level of nuclear power plants and providing guarantees for the safe operation of nuclear power plants.
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Key words:
- Nuclear power plant /
- Expert knowledge database /
- Chemical control /
- Anomaly detection /
- Fault diagnosis
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图 2 人工排查过程
PI系统—OSIsoft 公司开发的工厂实时数据集成、应用平台；c—用户设定判断故障的阈值
Figure 2. Manual Troubleshooting Process
图 4 核电厂化学控制异常检测与故障诊断系统架构设计
Figure 4. Architecture Design of Chemical Control Anomaly Detection and Fault Diagnosis System for Nuclear Power Plants
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