Study on Condition Detection of Major Equipment in Nuclear Power Plants Based on Fuzzy Synthetic Assessment
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摘要: 针对核电厂重大设备管理细则、设备运行特点和要求,提出了核电厂的重大设备健康状态综合评价方法。根据核电厂设备状态监测特点,建立了基于监测任务的多层次指标体系模型。基于设备零部件潜在故障模式分析故障现象,分析设备监测任务,并构建监测任务隶属度函数模型。总结专家实际评估经验,提出指标权重由所辖多个监测任务共享,由劣化最严重的监测任务继承权重,得到设备的指标状态;通过改进的层次分析法,分配各指标的初始权重,并提出基于指标状态等级的分级变权理论模型,均衡考虑关键指标的恶化情况。将建立的评价方法应用于核岛主泵轴封系统健康状态评估,结果表明该方法可靠实用,能够有效表征重大设备的实际运行健康状态。Abstract: Focusing on the major equipment management detailed rules, equipment operation characteristics and requirements of nuclear power plants, a comprehensive evaluation method for major equipment health status of nuclear power plants is proposed. According to the characteristics of equipment monitoring of nuclear power plants, a multi-level indicator system model based on monitoring tasks is established. Based on the potential failure modes of equipment components, the fault phenomena and the equipment monitoring tasks are analyzed, and the monitoring tasks membership function models are constructed. Summarizing the practical assessment experience of the experts, this paper presents that indexes weight are shared by the multiple monitoring tasks, the weights are inherited by the most severely degraded monitoring task, and the indicator status of the equipment is obtained. Through the improved Analytic Hierarchy Process, the initial weights of each indicator are assigned, and the hierarchical variable weight theory models based on the indicator status level are proposed with a balanced consideration of the key indicators deterioration. The established evaluation method is applied to the health status assessment of the nuclear island main pump shaft seal system. The results show that the method is reliable and practical, and can effectively characterize the actual operational health status of major equipment.
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