针对750 k V变电站线路的复杂性、双重化保护配置,以及异常时报警信息量庞大和传统故障诊断中诊断信息源不全面等特点,提出了基于粗糙集和灰关联分析的冗余保护配置的750 k V变电站故障诊断方法。该方法根据750 k V变电站的电压等级特性...针对750 k V变电站线路的复杂性、双重化保护配置,以及异常时报警信息量庞大和传统故障诊断中诊断信息源不全面等特点,提出了基于粗糙集和灰关联分析的冗余保护配置的750 k V变电站故障诊断方法。该方法根据750 k V变电站的电压等级特性,将其划分为3个区域,并根据每个区域的接线特点进行分区处理。再利用故障录波信息和双套保护信息,基于粗糙集的知识获取方法构建诊断决策表,通过简化决策表,获得最小属性约简表。在此基础上建立比较序列与参考序列,采用灰关联分析确定约简表中属性的灰关联度和决策属性中可疑故障元件的灰关联可信度,获得明确的诊断结果。仿真结果表明该方法降低了变电站的网络拓扑结构和求解的复杂度,提高了对诊断知识的分类和识别能力以及诊断效率。展开更多
Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a...Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a full-scope,plant-wide fault diagnostic system.However,most of the proposed diagnostic techniques are perceived as unreliable by operators because they lack an explanation module,their implementation is complex,and their decision/inference path is unclear.Graphical formalism has been considered for fault diagnosis because of its clear decision and inference modules,and its ability to display the complex causal relationships between plant variables and reveal the propagation path used for fault localization in complex systems.However,in a graphbased approach,decision-making is slow because of rule explosion.In this paper,we present an enhanced signed directed graph that utilizes qualitative trend evaluation and a granular computing algorithm to improve the decision speed and increase the resolution of the graphical method.We integrate the attribute reduction capability of granular computing with the causal/fault propagation reasoning capability of the signed directed graph and comprehensive rules in a decision table to diagnose faults in a nuclear power plant.Qualitative trend analysis is used to solve the problems of fault diagnostic threshold selection and signed directed graph node state determination.The similarity reasoning and detection ability of the granular computing algorithm ensure a compact decision table and improve the decision result.The performance of the proposed enhanced system was evaluated on selected faults of the Chinese Fuqing 2 nuclear reactor.The proposed method offers improved diagnostic speed and efficient data processing.In addition,the result shows a considerable reduction in false positives,indicating that the method provides a reliable diagnostic system to support further intervention by operators.展开更多
文摘针对750 k V变电站线路的复杂性、双重化保护配置,以及异常时报警信息量庞大和传统故障诊断中诊断信息源不全面等特点,提出了基于粗糙集和灰关联分析的冗余保护配置的750 k V变电站故障诊断方法。该方法根据750 k V变电站的电压等级特性,将其划分为3个区域,并根据每个区域的接线特点进行分区处理。再利用故障录波信息和双套保护信息,基于粗糙集的知识获取方法构建诊断决策表,通过简化决策表,获得最小属性约简表。在此基础上建立比较序列与参考序列,采用灰关联分析确定约简表中属性的灰关联度和决策属性中可疑故障元件的灰关联可信度,获得明确的诊断结果。仿真结果表明该方法降低了变电站的网络拓扑结构和求解的复杂度,提高了对诊断知识的分类和识别能力以及诊断效率。
基金supported by the project of State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment(No.KA2019.418)the Foundation of Science and Technology on Reactor System Design Technology Laboratory(HT-KFKT-14-2017003)+1 种基金the technical support project for Suzhou Nuclear Power Research Institute(SNPI)(No.029-GN-B-2018-C45-P.0.99-00003)the project of the Research Institute of Nuclear Power Operation(No.RIN180149-SCCG)
文摘Scheduled maintenance and condition-based online monitoring are among the focal points of recent research to enhance nuclear plant safety.One of the most effective ways to monitor plant conditions is by implementing a full-scope,plant-wide fault diagnostic system.However,most of the proposed diagnostic techniques are perceived as unreliable by operators because they lack an explanation module,their implementation is complex,and their decision/inference path is unclear.Graphical formalism has been considered for fault diagnosis because of its clear decision and inference modules,and its ability to display the complex causal relationships between plant variables and reveal the propagation path used for fault localization in complex systems.However,in a graphbased approach,decision-making is slow because of rule explosion.In this paper,we present an enhanced signed directed graph that utilizes qualitative trend evaluation and a granular computing algorithm to improve the decision speed and increase the resolution of the graphical method.We integrate the attribute reduction capability of granular computing with the causal/fault propagation reasoning capability of the signed directed graph and comprehensive rules in a decision table to diagnose faults in a nuclear power plant.Qualitative trend analysis is used to solve the problems of fault diagnostic threshold selection and signed directed graph node state determination.The similarity reasoning and detection ability of the granular computing algorithm ensure a compact decision table and improve the decision result.The performance of the proposed enhanced system was evaluated on selected faults of the Chinese Fuqing 2 nuclear reactor.The proposed method offers improved diagnostic speed and efficient data processing.In addition,the result shows a considerable reduction in false positives,indicating that the method provides a reliable diagnostic system to support further intervention by operators.
