某核电厂蒸汽发生器水室内松脱事件诊断

某核电厂在热态性能试验（简称热试）期间出现蒸汽发生器松脱部件报警事件,为探究松脱部件报警原因以及评估设备损害程度,需对松脱部件进行及时确认。通过建立松脱部件诊断分析模型,对松脱事件发生时的原始数据进行详细分析,估计了松脱信号的传播速度、松脱部件质量和能量,最后评估了此次松脱报警事件的危害性。结果表明,蒸汽发生器内存在的松脱部件为游动的金属部件,该部件是反应堆内部结构脱落部件,其撞击频率为8700~9300 Hz,碰撞加速度峰值范围为3g~90g,松脱信号传播群速度为3200~3300 m/s,估计松脱部件质量约0.1 kg,撞击能量为0.45~0.89 J;质量和能量诊断结果与实际符合较好,表明本文提出的质量和能量估计方法是有效的。      

Development of integrated automatic diagnosis method for loose parts monitoring system

Generally, it is known that loose parts in the reactor coolant systems (RCS) bring serious damage into the system components and impede the normal function of the system. So, it is necessary to rapidly respond when the impact event has occurred. This paper presents a realization of automatic diagnosis algorithm for LPMS (Loose Parts Monitoring System) and application results to the impact test data at YongGwang Nuclear Power Plant Unit 3 (YGN3), Kori Nuclear Power Plant Unit 4 (KNU4) and the real data at YongGwang Nuclear Power Plant Unit 1 (YGN1). The integrated diagnosis algorithm is composed of three parts; prefiltering, impact location and mass estimation. The prefiltering is needed to reject low frequency background noises. To estimate the impact location, the starting points of impact are detected from the filtered signals and compared to produce the time differences, and then the modified triangular method is applied. To estimate the mass and energy of a loose part, we automatically compute the maximum amplitude and the initial half period. Additionally, a modified impact theory considering amplitude and energy attenuation effects is applied.

To show the effectiveness of the proposed diagnostic method, the real impact test data at YGN3, KNU4 and the real impact data at YGN 1 is used. The analysis results show that the location estimation error is on average below 7.5%, and the average mass estimation is within 40%.     

核电站中跌落零件冲击信号的时频综合报警方法

在对核电站中跌落零件冲击信号和复杂背景噪声进行时域分析和周围图法功率谱估计的荐,提出了跌落零件时频综合报警方法。该方法首先将背景噪声带通滤波,然后对信号时域预报警及频域报警确认。     

Experience with identification of loose parts by acoustic monitoring of primary system

Substantial progress has been achieved in the identification of loose parts which had been detected by acoustic monitoring of reactor primary system. Several years of practical experience and the use of the offline digital analysis system MEDEA proved that acoustic monitoring is very successful for detecting component failures at an early stage. ISTec is involved in loose parts monitoring in several nuclear power plants in Germany. Advanced powerful tools for classification and evaluation of burst signals have been realised.

Loose parts monitoring systems, which are installed in all German nuclear power plants (NPPs), indicated specific impact conditions at lower plenum of two BWR's. Flow tests were carried out with various coolant flow rates of internal axial pumps and use of model nuts in one case. More than 2000 different bursts have been analysed to provide information in detail about impact occurrences, their spectral characteristics and impact sequences. Burst shape parameters could be determined and signal amplitudes have been trended. Determination of the sound origin — fixed origin in one case, flow-induced moving origin in the other case - and mass estimation of the loose parts could be performed by application of advanced burst analysis methods. Characteristics of the impact signals are presented in the paper.     

核电站松动件碰撞特性物理模型研究

结合固体内弹性波传播特性,并根据核电站一回路内松动件碰撞的物理机制,在频域内建立了描述松动件碰撞特性的物理模型。对于松动件碰撞接触力的数学描述,作出了与一般文献中假设的半正弦波函数关系不同的半正弦波平方的函数关系假设。根据Hertz碰撞理论和该模型,可对松动件碰撞质量进行计算。实验证明该物理模型能够描述核电站松动件碰撞特性,并且质量估计结果也是合理的,为核电站松动件故障诊断提供了一种手段。     

防城港核电站堆内中子通量测量系统指套管碰磨分析

防城港核电站1号机组主泵惰走试验期间,在对核电站松脱部件和振动监测系统13路加速度通道进行背景噪声例行检查时发现,通过松脱部件和振动监测系统的声音监听设备监测到,安装于反应堆压力容器底部堆内中子通量测量系统导向管上通道有"哒哒哒"的异常信号。为找出异常信号源,利用松脱部件监测系统声监测功能对压力容器底部监测到的异常信号进行分析,该信号不是由松脱部件产生的信号。通过听音棒的辅助监听,最后综合分析得出该信号是由堆内中子通量测量系统指套管在管道路径上碰磨引起。该事件的分析与解决,不仅解决了工程建设需要,对核安全局批准下一步工作开展提供了支持依据,而且对通过松脱部件监测系统来开展由于流致振动引起的中子通量测量系统指套管异常振动诊断有重大的实用价值。     

压水堆－回路系统松动部件故障的噪声分析及模拟试验

松动部件监测的基本原理是应用加速度计测量金属松动部件碰撞产生的结构传递声，通过微处理机的软、硬件系统进行识别和诊断。本文介绍了松动部件监测的理论基础、松动部件的定位和质量估计、应用噪声分析技术进行的三个模拟试验。本文为研制松动部件监测系统做了一些前期工作。     

核电厂松脱事件报警及应急响应研究

通过对松脱部件事件报警逻辑及国内外松脱部件监测法规和标准中关于松脱事件报警及应急响应的研究,结合国内某核电厂热试期间发生的松脱事件报警及报警事后应急响应,详细分析了该核电厂松脱事件过程。松脱事件报警分为绝对阈值和相对阈值报警,本文提出在系统报警逻辑中增加了计数因子和通道复核来提高报警准确率;GB/T 11807、IEC 60988和ASME均要求事件报警后采取措施确定报警是否是松脱部件所致,以及松脱部件对反应堆一回路系统产生的潜在危害进行评估;RG 1.133则要求确认松脱事件报警后应上报核管理委员会,GB/T 11807和IEC 60988则根据具体运行电厂确定,对于是否上报未做明确规定。基于国内某核电厂出现松脱事件报警及其应急响应,建议建立适合于国内核电厂松脱事件报警及应急响应机制,对于运行中出现的松脱事件及时确认,并对设备部件可能造成的损失情况进行及时评估,并对是否上报及采取何种措施做出进一步的规定。      

Acceleration Signal Characteristics for Loose Part Impact

Characteristics of acceleration frequency spectra for an impact signal were studied and loose part mass was estimated, using variation in the frequency spectral patterns. The frequency spectral pattern for the acceleration induced by impact depends on the loose part mass and not on the impact energy and the loose part shape. It was found that the frequency spectral pattern for an impact which occurred at the lower plenum vessel wall is not influenced by the impact point. On the other hand, the maximum acceleration amplitude depends not only on the loose part mass but also on the impact energy, the loose part shape and the distance from the impact point. It was also found that the foremost portion of the accelerometer output signal is influenced by the impact force between a loose part and the vessel. However, a second portion is influeuced by the sensor resonance and structural resonances. Loose part mass estimation, using “FR” values (ratio between low frequency component and high frequency component), is useful. The uncertainty range for the estimated loose part mass is about 0.7 decade.     

基于连续小波变换的Hilbert包络线松动部件定位方法

本文结合时-频域信号处理方法,在对冲击信号进行连续小波变换(CWT)的基础上,采用计算信号Hilbert包络线极大值的方法确定冲击信号的到达时间,并应用于网格定位。研究结果表明,该方法具有较高的定位精度,对小质量的松动部件能准确地定位其位置,且具有较好的抗噪能力。     

Loose-part signal properties

Lamb's solution for two-dimensional wave propagation was used to identify plate bending wave characteristics observed in loose part impact signals. The surface displacement wave is shown to have large second derivatives at points that can be used to measure the impact contact time. General features of the initial impact wave shape provide guidance for the use of spectral analysis techniques to identify the contact time and wave arrival time when there is a low signal-to-noise ratio. Improvements in the determination of contact time improve the estimation of loose part mass and energy through the Hertz impact parameters. The shape of the initial impact wave shape can also be used to identify on which side of the plate the impact took place. This information has applications for Loose Part Monitoring System metal impact signal validation and for improved estimation of loose part parameters.     

基于神经网络的松动部件监测系统小波质量估计方法研究

采用基于神经网络的小波质量估计方法对松动部件检测系统中小质量的螺钉(5g)、螺母(12g)和钢球(4．5g)进行了实验研究。结果表明：该方法能较好地区分不同质量的螺钉、螺母和钢球。     

基于盲源分离算法的压水堆松动件信号提取方法

压水堆一回路松动件状态监测系统的关键环节在于如何从复杂背景噪声中提取松动件冲击信号。利用基于最大信噪比的盲源分离算法,将压水堆背景噪声和松动件冲击信号从观测到的混合信号中分离,并利用相似系数对该算法的分离效果进行了评估。根据该算法,当分离信号之间关系均独立时,信噪比函数取得最大值。研究结果表明,该算法可高效、准确地实现压水堆一回路松动件冲击信号和背景噪声信号的分离。     

基于自适应阈值的小波包在松动部件信噪分离中的研究

研究了反应堆主回路系统背景振动噪声的特点。在传统松动部件信号提取方法的基础上,利用对小波包系数加入时间窗的方法实现对去噪阈值进行自适应选取。同时采用了一种新的阈值处理函数对含噪声的松动部件冲击信号进行去噪处理,并对模拟实验装置上采集到的钢球冲击信号进行分析。实验结果表明,本文提出的方法能有效跟踪背景噪声强度的变化,有效抑制背景噪声,准确识别松动部件冲击信号,提取相关特征。     

Modern methods of signal processing in the loose part monitoring system

The loose part monitoring system (LPMS) in the primary circuit of the WWER-440/WWER-1000 as in any other PWR or BWR type of NPP is one of the fundamental and essential to safety diagnostic tools. The purpose of the system is to detect, localize and analyze detached or loose metal pieces. When the metal impact occurs it causes the mechanical vibration of the structures and sensors detect a burst signal. The aim of this work is to show the potential of using modern signal processing methods in enhancing the LPMS performance by solving the tasks of noise cancellation, time of arrival detection, discrimination between real and faulty alarms, and loose metal piece mass estimation.     

基于自适应AR模型的核电站松动件报警方法

为能快速准确地检测到核电站一回路零部件的松动或脱落,提出1种基于自适应AR（auto-regressive）模型的松动件报警方法。该方法利用自适应AR模型跟踪一回路中背景噪声的变化,先对信号进行白化处理,再计算白化后信号的短时均方根（RMS）,设置RMS动态阈值实现报警。采用秦山核电站一号机组背景噪声和松动件碰撞信号叠加进行了仿真试验,结果表明,该方法能够在低信噪比和噪声复杂变化的条件下快速检测出松动件碰撞信号。     

Development of automatic algorithm for localizing loose parts with a steam generator

In this paper, an automatic localization algorithm for estimating the impact location by loose parts in a Steam Generator using modified triangular method is proposed and applied to the impact test data of YongGwang Nuclear Power Plant Unit 3 Steam Generator. The algorithm, at first, was developed at the Mock-up system and modified to apply for the real plant. The Steam Generator is modeled as a cylinder shape and the modified method is used to find out the impact point of a loose part on the model. The result of estimated impact point applying to the developed algorithm has below about 5% average error. If the algorithm will be installed in the existing plant or next generation plant, the safety and reliability of Nuclear Power Plant will be improved.     

大亚湾核电站松动部件监测系统的误报警处理

大亚湾核电站松动部件在线监测系统投入运行以来，曾因频繁误报警而不断地改进。在2号机组第四燃料循环系统出现了持续的误报警，因系统存在设计缺陷，在停机小修期间采用加速度传感器的方法进行故障诊断。结果表明．持续报警不是由松动部件引起的，它来自主泵的噪声，系统本身的缺陷需要进行改造。     

控制棒驱动机构备件数量优化方法

控制棒驱动机构是反应堆控制和保护系统的伺服机构,是执行反应堆功率调节、紧急停堆的重要核安全设备。控制棒驱动机构成本较高,如何合理确定其备件数量对于提高反应堆的可运行性具有重要意义。本文针对控制棒驱动机构,在系统连续运转时间不小于换料周期的约束条件下,提出了一种确定控制棒驱动机构备件数量的优化方法--分组备件数量优化方法,给出了总费用最少的各子系统的备件配置方案。通过随机模拟计算对分组备件数量优化方法与常规算法进行比较,结果表明：该方法常优于常规算法,在保证控制棒驱动机构可用性的前提下,优化备件数量配置可降低成本。该优化方法同样适用于其他设备的备件分析,对工程中设备备件的分析与研究具有指导意义。     

Algorithm automation for nuclear power plant Loose Parts Monitoring System

Loose Parts Monitoring signals in the control room of the nuclear power plant come in through multiple channels and are presented as graphs on the display devices. It involves a lengthy and complicated process to determine the size, mass, speed, and impact location of the loose part when the signals are collected and processed. In this work, a simple and efficient model for determining the impact location of the loose part using the Least-Sum-of-Square-Errors (LSSEs) method combined with iteration has been developed based on the phase distortion of the impact signal envelopes. The signal peak point shifts to the right on the time axis when the sensor is located farther away from the impact location. This method provides a good estimation of the impact location and can be used as an alternative to existing calculations based on other attributes of the impacting signal. To automate the backend portion of the LPMS algorithm, interpolation was used for compensating the impact attenuation effect and log-log regression was also employed to determine the impacting part size and impact velocity, and the result turned out to be well in line with the manual calculations. The automated algorithm will improve the efficiency of the LPMS software.