基于模糊距离的核电厂瞬态分段识别方法

近年来发展的核电厂瞬态识别技术,可为操纵员提供处于发展阶段的故障信息,有助于了解核电厂状态并及时采取相应的操作动作,保证核电厂的安全运行。将瞬态过程曲线分为两段,前段利用聚类方法用于快速识别,后段利用提取的瞬态过程的特征进行更准确的识别。利用待识别瞬态与参考瞬态间的模糊距离描述二者的相近程度,可以消除噪声等扰动的影响,并得到更符合认知习惯的结果。利用高温气冷堆核电厂仿真机的故障数据验证瞬态识别方法的有效性。     

基于模糊距离的核电厂瞬态分段识别方法

近年来发展的核电厂瞬态识别技术,可为操纵员提供处于发展阶段的故障信息,有助于了解核电厂状态并及时采取相应的操作动作,保证核电厂的安全运行。将瞬态过程曲线分为两段,前段利用聚类方法用于快速识别,后段利用提取的瞬态过程的特征进行更准确的识别。利用待识别瞬态与参考瞬态间的模糊距离描述二者的相近程度,可以消除噪声等扰动的影响,并得到更符合认知习惯的结果。利用高温气冷堆核电厂仿真机的故障数据验证瞬态识别方法的有效性。     

基于图像熵的数字化核电站人机界面复杂度快速评价

计算机画面是数字化核电站人机界面的基本组成元素,画面的复杂程度会影响操纵员对核电站情况的掌握。为对单幅画面进行快速有效的复杂度定量评价,本文提出了一种基于图像熵的定量评价方法。首先对画面做图像化处理,并转化为灰度图,然后利用图像熵的定义,计算整个画面的熵值,并将其作为画面复杂度的度量。实验结果表明,图像熵作为画面复杂度的定量评价指标,与人工评价结果具有一致性,能反映人对画面复杂度的综合感受。此方法可应用于实际工程设计,特别是在设计初期不具备实验评价和专家评价的条件时,用来对画面进行复杂度测量,可避免画面过度复杂、改善人机交互。     

电磁轴承保护轴承在线衰退评估研究

保护轴承是电磁轴承结构的最后一道安全屏障。由于拆机检查成本较高,且因为保护轴承的特殊性,拆机后单独对保护轴承检查难以判断其还能否继续工作,迫切需要一种在线评估方法。本文首先开展电磁轴承高速跌落试验,直到某型号保护轴承完全失效。记录每次高速跌落前转子低速跌落过程中的位移数据。基于上述数据,分别应用多尺度排列熵、马氏距离、多尺度模糊熵等方法,研究保护轴承随着高速跌落次数增加的衰退规律。研究发现,应用多尺度模糊熵指标可反映多次高速跌落后保护轴承性能的衰退,实现对保护轴承性能在线评估。马氏距离指标也可用于辅助判断,但效果不如多尺度模糊熵方法。而多尺度排列熵指标不适合这一应用。     

高温气冷堆核电站计算机化运行规程方案及异常事件处理规程入口识别

根据高温气冷堆核电站计算机化运行规程系统的设计准则,给出了高温气冷堆核电站计算机化运行规程的总体设计方案,指出计算机化运行规程系统的一个重要作用就是提供规程入口选择。高温气冷堆核电站的异常事件处理规程是基于事件的,因此选择规程入口的关键在于异常事件的识别。为解决该问题,采用具有图形描述能力和严密数学理论的模糊Petri网,构建了异常事件识别专家系统。相较于传统方法,模糊Petri网结构化特性和知识表达能力更强,推理效率大幅提高,便于计算机编程实现。通过典型异常事件识别的仿真,表明所构建的异常事件识别专家系统是合理可行的,为高温气冷堆核电站计算机化运行规程系统的研制打下了基础。     

基于运行过程变量特征分析的核级闸阀故障诊断方法

针对核级闸阀卡滞故障,提出一种基于运行过程变量特征分析的闸阀故障诊断方法。闸阀开关运行过程往往包含故障特点及变化规律,因此该方法首先利用Shannon熵对闸阀开关过程振动信号功率谱进行信息化度量,计算出功率谱熵均值作为目标过程变量,分析闸阀健康情况下和故障情况下的目标过程变量的特征变化,进而划分故障区域和非故障区域,对闸阀进行故障诊断。最后基于核级闸阀实验,对该方法进行实验验证,结果表明该方法能够有效地诊断出核级闸阀故障,并且该方法具有一定的故障预测能力。因此该方法的使用能够降低因为闸阀卡滞故障造成的核设施事故发生概率,同时该方法能够用于其他领域闸阀故障诊断。     

基于运行过程变量特征分析的核级闸阀故障诊断方法

针对核级闸阀卡滞故障,提出一种基于运行过程变量特征分析的闸阀故障诊断方法。闸阀开关运行过程往往包含故障特点及变化规律,因此该方法首先利用Shannon熵对闸阀开关过程振动信号功率谱进行信息化度量,计算出功率谱熵均值作为目标过程变量,分析闸阀健康情况下和故障情况下的目标过程变量的特征变化,进而划分故障区域和非故障区域,对闸阀进行故障诊断。最后基于核级闸阀实验,对该方法进行实验验证,结果表明该方法能够有效地诊断出核级闸阀故障,并且该方法具有一定的故障预测能力。因此该方法的使用能够降低因为闸阀卡滞故障造成的核设施事故发生概率,同时该方法能够用于其他领域闸阀故障诊断。     

模糊控制技术在核电站系统中的应用

在核电站系统中应用模糊控制技术是控制技术发展的新课题,研究分析国内外核电站系统中的模糊控制技术的应用发展是十分必要的。本文分析了模糊控制在核电站系统中的应用,分析结果表明模糊控制可以很好地提高核电站系统运行的稳定性和安全性,是一种有效并且可行的先进控制方法。国外核电站系统中应用成功的模糊神经网络技术融合了模糊控制与神经网络技术的优点,是一种新兴的控制技术,研究表明,在核电站系统中应用模糊神经网络技术可以大大提高反应堆运行的安全性和可靠性,具有广阔的应用前景。本文对模糊控制、模糊神经网络技术在核电站系统中应用的研究成果进行了全面回顾和总结,并探讨了在应用研究和实践中需要重点解决的问题。     

模糊神经技术在反应堆安全研究中的应用

概要介绍了模糊神经网络技术 ,并对其在核电厂的负荷跟踪、功率分布控制、运行状况及运行参数的虚拟测量、故障诊断及瞬态识别以及核燃料的质量检查等方面的应用情况进行了综述。模糊神经网络技术在核电厂中的应用大大提高了反应堆运行的安全性和可靠性 ,展现了良好的推广应用前景     

基于MAAP5程序的秦山核电站严重事故分析

应用MAAP5程序建立了秦山核电站一、二回路,安全系统以及安全壳的模型,并以冷段双端断裂叠加高高、高、低压安注失效,安全壳喷淋系统失效为例,对该严重事故序列进行了模拟计算,给出了瞬态过程一些重要参数随时间的变化规律。结果表明：在72 h内无能动干预手段的条件下,安全壳的完整性可得到保证,相关数据可为秦山核电站严重事故预防和事故缓解措施的制定提供重要参考。     

Identification of nuclear power plant transients using the Particle Swarm Optimization algorithm

In order to help nuclear power plant operator reduce his cognitive load and increase his available time to maintain the plant operating in a safe condition, transient identification systems have been devised to help operators identify possible plant transients and take fast and right corrective actions in due time. In the design of classification systems for identification of nuclear power plants transients, several artificial intelligence techniques, involving expert systems, neuro-fuzzy and genetic algorithms have been used. In this work we explore the ability of the Particle Swarm Optimization algorithm (PSO) as a tool for optimizing a distance-based discrimination transient classification method, giving also an innovative solution for searching the best set of prototypes for identification of transients. The Particle Swarm Optimization algorithm was successfully applied to the optimization of a nuclear power plant transient identification problem. Comparing the PSO to similar methods found in literature it has shown better results.     

利用可信性模糊回归模型研究核电厂操纵员事故响应时

利用模糊数学中的模糊数概念,采用可信性模糊回归模型研究核电厂操纵员的事故响应.对影响操纵员事故响应时间的绩效形成因子PSF进行了定量化的分析,得到了核电厂操纵员事故响应时间的可信性模糊回归模型定量计算公式.对所得到的结论进行了相应的分析,说明了在小样本情况下所采用研究方法的正确性.研究方法不仅对核电厂的安全运行可以提供相应的参考借鉴而且可以推广到其他研究领域.     

Evolutionary fuzzy clustering for the Classification of transients in nuclear components

The classification of objects or patterns is an important area of research with practical applications in a variety of fields. In this paper we are interested in the classification of signal transients for the reliable monitoring and timely diagnosing of nuclear components and systems. These represent fundamental tasks for the operation, control and accident management of nuclear power plants. The problem is tackled within a fuzzy clustering approach. The choice of the metrics upon which the clustering is based is critical for obtaining geometric clusters in the features space as close as possible to the real physical classes. In this respect, here the a priori known information regarding the true classes to which the objects belong will be exploited to select, by means of an evolutionary algorithm of literature, an optimal metrics for the clustering. In case the classification thereby obtained were still unsatisfactory, an iterative procedure is used to split the less compact physical classes in further subclasses.     

The fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for nuclear power plant site selection – a case study from Turkey

The location selection for nuclear power plant (NPP) is a strategic decision, which has significant impact on the economic operation of the plant and sustainable development of the region. This paper proposes fuzzy TOPSIS and generalized Choquet fuzzy integral algorithm for evaluation and selection of optimal locations for NPP in Turkey. Many sub-criteria such as geological, social, touristic, transportation abilities, cooling water capacity and nearest to consumptions markets are taken into account. Among the evaluated locations, according to generalized Choquet fuzzy integral method, Inceburun–Sinop was selected as a study site due to its highest performance and meeting most of the investigated criteria. The Inceburun-Sinop is selected by generalized Choquet fuzzy integral and fuzzy TOPSIS I?neada–K?rklareli took place in the first turn. The Mersin–Akkuyu is not selected in both methods.     

Experimental study of natural circulation instability with void reactivity feedback during startup transients for a BWR-type SMR

The natural circulation boiling type SMR can experience flow instability during the startup transients due to the void reactivity feedback. A BWR-type natural circulation test loop has been built to perform the nuclear coupled startup transient tests for Purdue Novel Modular Reactor (NMR). This test loop is installed with different instruments to measure various thermal hydraulic parameters. The testing process can be monitored and controlled through PC with the assistance of LabVIEW procedure. The effects of power ramp rate on the flow instability during the nuclear coupled tests were investigated by controlling the power supply based on the point kinetics model with coolant void reactivity feedback. Two power ramp rates were investigated and the results were compared with those of the thermal hydraulic startup transients without void reactivity feedback. The time trace of power supply, system pressure, natural circulation rate, and void fraction profile are used to determine the flow stability during the transients. The results show that nuclear coupled startup transients also experience flashing instability and density wave oscillations. The power curves calculated from point kinetics model for startup transients show some fluctuations due to void reactivity feedback. However, the void reactivity feedback does not have significant effects on the flow instability during the startup procedure for the NMR.     

基于粗糙决策模型的核电厂故障诊断方法

将粗糙集和信息熵相结合,提出了改进的决策树ID3算法,并提出了基于此算法和粗糙集约简算法的故障诊断方法.将该方法用于核电厂故障诊断.结果表明,该方法具有良好的故障诊断性能,可在核电厂故障诊断领域中应用.     

核反应堆堆芯功率模糊切换控制系统开发及应用

为利用不同类型控制器的性能优势,基于堆芯模糊多模型,利用比例-积分-微分(PID)控制器和模糊控制器,结合T-S型模糊规则设计模糊切换控制器。以三里岛核电站压水堆堆型堆芯为例,建立一套堆芯功率模糊切换控制系统并开展仿真研究。结果表明,与传统PID控制器相比,所设计的堆芯模糊切换控制器更适用于堆芯反应性阶跃扰动和堆芯冷却剂进口温度阶跃扰动下的堆芯功率控制。     

模糊鲁棒控制方法在核反应堆功率控制中的应用

为了对核反应堆功率进行实时控制,以适应电网负荷的变化需求,基于T-S模糊模型设计了核反应堆功率模糊鲁棒控制器。首先使用状态反馈设计了局部控制器,然后应用并行补偿方法设计全局控制器。线性矩阵不等式的求解证明所设计的控制器是稳定的。仿真结果表明,对于3种典型工况变化,所设计的控制器对反应堆的功率变化能进行很好的控制。     

TRAC-PF1/MOD1 calculations and data comparisons for mist small-break LOCA, feed-and-bleed and steam-generator tube-rupture experiments

Los Alamos National Laboratory is a participant in the Integral System Test (IST) program initiated in June 1983 for the purpose of providing integral system test data on specific issues/phenomena relevant to post-small-break loss-of-coolant accidents, loss of feedwater and other transients in Babcock and Wilcox (B&W) nuclear plant designs. The Multi-Loop Integral System Test (MIST) facility is the largest single component in the IST program. MIST is a 2 × 4 [two hot legs and steam generators (SGs), four cold legs and reactor coolant pumps] representation of B&W lowered-loop reactor systems. It is a full-height, full-pressure facility with 1/817 power and volume scaling. Efforts are under way at Los Alamos to assess TRAC-PF1/MOD1 against data from the MIST facility.Calculations and data comparisons for TRAC-PF1/MOD1 assessment are presented for three transients run in the MIST facility. The energy removal and depressurization mechanisms in these tests are identified and the phenomena occurring in these tests compared. The tests analyzed are MIST Test 3109AA, the nominal small-break LOCA, Test 330302, a feed and bleed test with delayed high-pressure injection; and Test 3404AA, an SG tube-rupture test with the affected SG isolated. TRAC was able to predict these phenomena although the timing and magnitude of events were not always in good agreement.The MIST test have demonstrated the thermal-hydraulic phenomena expected to occur during transients in B&W nuclear plants. Because of scaling atypicalities, test results cannot be extrapolated directly to plant conditions. Although the phenomena were demonstrated in the MIST tests, there may be differences in the timing, magnitude and sequences of events in plant transients. Assessment calculations, three of which are presented here, have shown that the TRAC computer code can predict the major trends and phenomena occurring during the MIST tests with reasonable qualitative agreement. This includes complex sequences of events. Reasonable qualitative agreement is defined as meaning that major trends are predicted correctly, although TRAC values are frequently outside the range of data uncertainty. These assessment results, taken with assessment results from other facilities at a wide range of scales, provide us with confidence that the TRAC code can adequately simulate the transient phenomena possible in B&W nuclear plants.     

基于时间序列神经网络的蒸汽发生器传热管泄漏程度诊断研究

针对蒸汽发生器U形传热管泄漏,本文提出了一种基于时间序列神经网络对蒸汽发生器传热管泄漏程度进行诊断研究的方法。首先,对核电厂蒸汽发生器U型传热管泄漏进行机理分析,构建其数学模型,提取其泄漏的直接特征参数,再依据Fisher得分法,提取其间接特征参数;其次,通过滑动时间窗口法从预处理后的时间序列数据中生成数据样本,作为时间序列神经网络的输入,并以蒸汽发生器U形传热管泄漏程度信息为标注,基于反向传播（BP）算法对五层神经网络系统进行训练,得到蒸汽发生器U形传热管泄漏的时间序列神经网络模型;最后,模拟核电厂运行过程蒸汽发生器U形传热管泄漏时的时间序列测试数据。仿真结果表明,时间序列神经网络对演变事件的处理具有较好的有效性和较高的泛化能力,对故障程度的诊断研究具有参考价值。