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Reliability forecasting for operators' situation assessment in digital nuclear power plant main control room based on dynamic network model

机译:基于动态网络模型的数字核电站主控室操作员状况评估可靠性预测

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摘要

With the technical development of computer hardware and software, digitalization is a trend in large-scale complex systems such as nuclear power plants (NPPs). It changes the way main control room (MCR) operators interact with systems. Faced with these technical changes, operators need to continue improving their situation assessment (SA) reliability level. In addition to evaluate operators' SA reliability, managers and shift supervisors also want to forecast their SA reliability level. There have been many studies with respect to operators' SA, but most of them are static analysis method and cannot be applied to predict operators' SA reliability. So, on the basis of different forecasting approaches and observation data, how to predict the operators' SA reliability level has became a problem that many analyst interest in. In this paper, first we identified the influence factors associated with SA reliability, and then we developed the SA reliability model, finally we proposed a reliability forecasting model by integrating time series forecasting method with dynamic network model (DNM). Our experiment verification focused on steam generator tube rupture (SGTR) event, using the forecasting model, we demonstrated how to predict operators' SA reliability during the course, and the prediction results are consistent with measurement results. (C) 2015 Elsevier Ltd. All rights reserved.
机译:随着计算机硬件和软件技术的发展,数字化已成为诸如核电厂(NPP)之类的大型复杂系统的趋势。它改变了主控制室(MCR)操作员与系统交互的方式。面对这些技术变化,运营商需要继续提高其状况评估(SA)的可靠性水平。除了评估运营商的SA可靠性外,经理和值班主管还希望预测其SA可靠性水平。关于运营商SA的研究已经很多,但是大多数都是静态分析方法,不能用于预测运营商SA的可靠性。因此,基于不同的预测方法和观测数据,如何预测运营商的SA可靠性水平已成为许多分析师关注的问题。在本文中,我们首先确定了与SA可靠性相关的影响因素,然后我们确定了影响SA可靠性的因素。开发了SA可靠性模型,最后将时间序列预测方法与动态网络模型(DNM)相集成,提出了可靠性预测模型。我们的实验验证集中在蒸汽发生管破裂(SGTR)事件上,使用预测模型,我们演示了如何预测操作人员在整个过程中的SA可靠性,并且预测结果与测量结果一致。 (C)2015 Elsevier Ltd.保留所有权利。

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