Wavelet decomposition and radial basis function networks for systemmonitoring

Two approaches are coupled to develop a novel collection of black box models for monitoring operational parameters in a complex system. The idea springs from the intention of obtaining multiple predictions for each system variable and fusing them before they are used to validate the actual measurement. The proposed architecture pairs the analytical abilities of the discrete wavelet decomposition with the computational power of radial basis function networks. Members of a wavelet family are constructed in a systematic way and chosen through a statistical selection criterion that optimizes the structure of the network. Network parameters are further optimized through a quasi-Newton algorithm. The methodology is demonstrated utilizing data obtained during two transients of the Monju fast breeder reactor. The models developed are benchmarked with respect to similar regressors based on Gaussian basis functions     

基于平稳小波变换的毛刺检测算法

核爆炸地震监测技术研究中,数据质量检测是地震数据自动处理的基本内容,毛刺是影响数据质量的主要问题数据。基于平稳小波变换和非线性能量检测算法,给出一种毛刺自动检测算法。平稳小波变换弥补了正交小波变换存在的不足,可以使尺度分解结果的长度和原始数据保持一致,具备时移不变性。非线性能量检测算法可以增强记录中的高频信号,对平稳小波变换的结果应用非线性能量检测算法,提高了记录中毛刺检测的准确性,非常适合连续地震监测数据自动处理的需要。实验结果表明,给出的这种算法特别有利于记录中小毛刺的检测,从而能够减小信号检测的误检率。     

基于小波的突变信号识别方法及应用研究

小波的空间局部性使它能聚焦于信号的局部结构,用来确定信号的突变性位置。但进一步研究发现,小波变换改进的单子带算法虽能有效识别第1类突变点,但对于第2类突变点却无法有效识别,且二进离散小波变换的快速算法还存在频率混淆等问题。通过深入研究提出了引入过渡函数的单子带重构的改进算法,解决了第2类突变信号的准确识别问题,通过相关实验验证了该方法能较好地解决主泵转子刚度突变等信号的有效识别问题。     

Incipient fault detection of motor-operated valves using wavelet transform analysis

The necessity of improvements in monitoring and diagnosis methods started to be of extreme relevance in the predictive maintenance field, establishing the reliability and readiness of system components as an achievable goal. Taking into account these reasons, this paper presents an approach for incipient fault detection of motor-operated valves (MOVs) using wavelet transforms. The technique applied in this paper is the wavelet transform analysis using wavelet toolbox, where the main goal is to obtain more detailed information contained in the measured data, identifying and characterizing the transient phenomena in the time and frequency domains, correlating them to failure situations in the incipient stage. The wavelet analysis has provided good results establishing a new qualitative methodology for monitoring and diagnostics of motor-operated valves.     

核爆电磁脉冲信号的分形特征分析

针对核爆电磁脉冲(NEMP)信号的非平稳、非线性特点．将小波变换和分形方法引入到NEMP信号的分析处理中,提取了多分辨率能量分形特征及盒维数．并在实验的基础上对所提取的特征与NEMP传播距离及当量之间的关系进行了分析．从而为NEMP信号分析与处理提供了一种新的方法。     

High Counting Rate Spectrometer

A signal processing system is proposed, capable of accepting a counting rate which is limited only by the charge collection time of the detector and by the time of the sample-hold circuits employed. This system has not been assembled. The concept is presented in order to stimulate interest and development by others.     

Consistent output estimate with wavelets: An alternative solution of least squares minimization problem for identification of the LZC system of a large PHWR

A novel technique for estimating system parameters based on consistent output estimate in wavelet domain is proposed as an alternative solution to the classical least squares minimization problem, in this paper. The algorithm is computationally efficient and exhibits excellent performance in cross validation. An iterative algorithm, alternately projecting the solution in time and wavelet domain for penalized minimization of local error in wavelet coefficients, is presented in the paper. As a case study, the paper addresses the problem of modeling a complex process in a large Pressurized Heavy Water Reactor (PHWR) based on the evolution of input and output. Xenon-induced spatial oscillations are kept from growing in large PHWRs, by means of the Liquid Zone Control System (LZCS). In this work, an identification scheme of a single input single output linear time invariant model of the LZCS is studied. Shift invariant orthogonal wavelets are used for consistent output estimate of the LZCS process. The technique is verified on the real experimental data obtained from the LZCS test set-up. It is observed that even a low order wavelet based model gives excellent approximation from fewer numbers of input–output data points.     

Monte Carlo simulation of nonlinear reactive contaminant transport in unsaturated porous media

In the current proposed solutions of radioactive waste repositories, the protective function against the radionuclide water-driven transport back to the biosphere is to be provided by an integrated system of engineered and natural geologic barriers. The occurrence of several nonlinear interactions during the radionuclide migration process may render burdensome the classical analytical–numerical approaches. Moreover, the heterogeneity of the barriers’ media forces approximations to the classical analytical–numerical models, thus reducing their fidelity to reality. In an attempt to overcome these difficulties, in the present paper we adopt a Monte Carlo simulation approach, previously developed on the basis of the Kolmogorov–Dmitriev theory of branching stochastic processes. The approach is here extended for describing transport through unsaturated porous media under transient flow conditions and in presence of nonlinear interchange phenomena between the liquid and solid phases. This generalization entails the determination of the functional dependence of the parameters of the proposed transport model from the water content and from the contaminant concentration, which change in space and time during the water infiltration process. The corresponding Monte Carlo simulation approach is verified with respect to a case of nonreactive transport under transient unsaturated flow and to a case of nonlinear reactive transport under stationary saturated flow. Numerical applications regarding linear and nonlinear reactive transport under transient unsaturated flow are reported.     

基于小波分析的粗晶材料超声无损评价信号处理技术

噪声是降低超声检测可靠性的因素之一。本文利用小波分析对粗晶材料超声检测中由晶界散射引起的结构噪声进行了分析处理。和小波变换相比,小波包变换频域分辨率高,在信号的分解,降噪和重构时性能比前者好。对奥氏体不锈钢中人工缺陷的Ａ型超声信号的处理结果表明,结果噪声被有效地滤除,且不损失缺陷信号,信噪比明显提高。     

粗晶材料超声检测信号处理

粗晶材料超声检测时,严重的结构噪声使信噪比很低。为了提高信噪比,增加粗晶材料超声检测的可靠性,人们在数字信号处理方法中做了大量工作。信号平均、滤波、卷积、频谱分析及时频分析等信号处理方法都获得过应用。小波分析是一种时频分析技术,具有自适应的带宽,适合于时变的超声缺陷信号的处理;用于粗晶材料的信号处理时,比其它方法获得的信息要丰富得多,且能大幅度提高信噪比。     

Thermal power estimation by fouling phenomena compensation using wavelet and principal component analysis

A small percentage of reactor thermal power can be overestimated because of fouling phenomena in a secondary feedwater flowmeter. This study proposes a signal processing technique for the compensation of a degraded flowmeter such a secondary feedwater flowmeter in nuclear power plants. The technique proposed is mainly focused on noise classification and step-by-step noise reduction. The noises focused are classified into the rapid distortion caused by environmental interference, the flow fluctuation according to plant state transition and the degradation by fouling phenomena qualitatively. The multi-step de-noising technique reduces each noise by three techniques step-by-step. The wavelet analysis as a low frequency pass filter to remove the rapid distortion, the linear principal component analysis (PCA) to predict a steady-state value from the fluctuation, and the non-linear PCA implemented as an autoassociative neural network (AANN) to predict an original value from the signal including fouling phenomena are developed. The main purpose of this approach is to make an AANN concentrate on compensating the degradation by fouling phenomena itself. For the demonstration the signals from a simulator and signal modeling were used so that the role and the performance of each noise removal step was represented. In addition a thermal power deviation estimator is proposed to recognize the degradation effect of each operating parameter for reactor thermal power calculation.     

Analysis of a signal during bistable flow events in Laguna Verde Nuclear Power Station with wavelets techniques

This paper is concerned about bistable flow, which is manifested by a small and spontaneous change in the recirculation loop flow that has been reported in some Boiling Water Reactors. Here some real time series of the bistable flow from the Laguna Verde Nuclear Power Plant (LVNPP) are analyzed using a methodology based on wavelet transform. This methodology involves the decomposition of the original signal using the Continuous Wavelet Transform (CWT) and the application of the Discrete Wavelet Transform (DWT) based on the Multiresolution Analysis (MRA). The CWT provides information about ruptures, discontinuities and fractal behavior. The MRA allows a fast implementation of the Discrete Wavelet Transform providing information about frequencies, discontinuities and transients that can be detected with analysis at different levels of details coefficients. The combination of both techniques allows the definition of an integral methodology for the study of reactor signals. We found that the associated frequencies for the singularities observed due to bistable flow for the case of LVNPP, correspond to the interval 0.01-0.1 Hz.     

Consistent generation of point feedback reactivity parameters for stability and thermalhydraulic codes

This paper shows a consistent methodology to obtain the point kinetics feedback reactivity parameters to be used by stability codes, like LAPUR-5, or transient codes, like TRAC-BF1. This methodology has been implemented in the code PAPU that generates the point kinetic parameters and feedback reactivity coefficients for the LAPUR and TRAC-BF1 codes. The results of the nodal reactivities obtained with the PAPU methodology have been compared with the results of other codes for different types of perturbations. Also, the reactivity tables generated by PAPU have been used in the LAPUR-5 code obtaining good results when the DR computed by LAPUR with these reactivity tables have been compared with the experimental DR obtained from signal analysis of Cofrentes NPP.     

基于小波独立成分分析的核动力装置冗余传感器故障在线诊断方法研究

针对核动力装置传感器的在线故障诊断问题,提出一种基于小波独立成份分析(WAV-ICA)的冗余传感器故障在线诊断方法。利用小波分解对测量信号进行高频滤波,消除电子噪声和传输噪声的影响,选取所关注的独立成分进行参数估计,并进行独立成分分析(ICA),从而实现对固定偏差、突变故障以及漂移故障的在线检测;利用稳压器5路冗余压力测量数据对该方法的故障检测效果进行验证,并与简单分析法(SA)和直接ICA方法进行对比分析。结果表明,该方法能有效地在线检测固定偏差和漂移故障,具有误诊率低、鲁棒性强、受单通道故障影响小的特点。     

Initial Test Results of the Omron Face Cue Entry System at the University of Missouri-Rolla Reactor

The University of Missouri-Rolla Reactor facility is testing, in collaboration with Omron Transaction Systems, Inc., the Omron Face Cue facial recognition system for access control to its restricted area. The installation of this system is the first of its kind at a security-relevant facility in the U.S. and within the research reactor community. The Face Cue is an on-demand device based on facial recognition and storage technology. The image processing methodology is as follows: (1) facial position detection, (2) background elimination, (3) facial features discrimination via application of a wavelet transform. The extracted facial feature values are compared to the data archived in its database and access is provided upon meeting the authorization criteria. The current test phase consisted of assessing the functionality of the Face Cue during daily use and in terms of its robustness (flexibility) as a function of the following physical parameters: (1) subject's distance away from the Face Cue, (2) ambient lighting conditions, (3) subject's facial orientation, (4) subject's facial expression and (5) peripheral facial features/modifications. The system has operated at nearly 100% reliability during several test intervals with approximately 7,000 entry attempts to date.     

液闪探测的时间分辨率研究

液闪探测系统设计中引入信号处理设计方法,经分析液闪探测信号,得出提高时间分辨率有利于提高探测效率的观点和实现方案,并获得了验证.据此,采用高速数字信号处理技术和器件,多道探测和复合探测效率也会相应提高.     

中低放固体放射性废物处置中的α废物在线检测及位置判定方法初探

根据在核废料回取分类、压缩减容的处置工艺及部分专用设备开发等方面的研究和初步实践,提出了利用现代测试技术和自动控制原理对a型废物进行在线探测、位置判定、目标成像、定性分析、比活度粗测的方法。     

Scaling of two-phase flow transients using reduced pressure system and simulant fluid

Scaling criteria for a natural circulation loop under single-phase and two-phase flow conditions are derived. Based on these criteria, practical applications for designing a scaled-down model are considered. Particular emphasis is placed on scaling a test model at reduced pressure levels compared to a prototype and on fluid-to-fluid scaling. The large number of similarity groups which are to be matched between model and prototype makes the design of a scale model a challenging task. The present study demonstrates a new approach to this classical problem using two-phase flow scaling parameters. It indicates that a real time scaling is not a practical solution and a scaled-down model should have an accelerated (shortened) time scale. An important result is the proposed new scaling methodology for simulating pressure transients. It is obtained by considering the changes of the fluid property groups which appear within the two-phase similarity parameters and the single-phase to two-phase flow transition parameters.Sample calculations are performed for modeling two-phase flow transients of a high-pressure water system by a low-pressure water system or a Freon system. It is shown that modeling is possible for both cases for simulating pressure transients. However, simulation of phase change transitions is not possible by a reduced pressure water system without distortion in either power or time.     

Applying particle swarm optimization algorithm for tuning a neuro-fuzzy inference system for sensor monitoring

A neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm has been developed for monitoring the relevant sensor in a nuclear power plant (NPP) using the information of other sensors. The antecedent parameters of the ANFIS that estimates the relevant sensor signal are optimized by a PSO algorithm and consequent parameters use a least-squares algorithm. The proposed methodology to monitor sensor output signals was demonstrated through the estimation of the nuclear power value in a pressurized water reactor using as input to the ANFIS six other correlated signals. The obtained results are compared to two similar ANFIS using one gradient descendent (GD) and other genetic algorithm (GA), as antecedent parameters' training algorithm.     

Response of proposed passive safety injection system for an intermediate size break LOCA on CHASNUPP-1

A passive safety injection system (PSIS) is proposed for Chashma nuclear power plant-1 (CHASNUPP-1) type nuclear power plants, for the simplification of their safety systems. This system is based upon passive components and is proposed in place of the existing safety injection system, for safety enhancement. The functionality of the proposed system is analyzed using reactor simulation. For this purpose an intermediate size break LOCA is simulated using the simulation software APROS. For this transient, different thermal-hydraulic parameters of the proposed and other safety related systems are presented and discussed. The results obtained show that the proposed system works properly by performing its role in the transient, leading to cold shutdown conditions.