Filtering properties of an adaptive trend operator and the application for determining the arterial blood velocity in retinal vessels

This study deals with methods focused on estimating blood velocity. The estimation of the linear trend function of a non-stationary signal based on the adaptive recursive estimation of the mean value function is used for the determination of the time delay of two indicator dilution curves. The filter property of this trend operator depends on the choice of a constant parameter c, the so-called adaptation factor. The functional connection between the filter property and the adaptation factor is considered in such a way that an objective calculation of arterial blood velocity in retinal vessels is possible.     

Approximation of Well Function and Identification of Leaky Aquifer Parameters

The existing equation for leaky aquifers is transformed into a nondimensional form using new parameters and a scaled well function for leaky aquifers is proposed. A computationally simple function is developed for accurately approximating the scaled well function for the practical range of the parameters. Utilizing this function (approximation), an optimization method is proposed for identifying the leaky-aquifer parameters from observed drawdowns. The new function has an enhanced utility when a repetitive numerical evaluation of the well function for leaky aquifers is needed, e.g., while estimating the aquifer parameters using optimization or Kalman filter or artificial neural network methods. The application of the proposed method is illustrated using a few sets of published data. The proposed method outperforms the extended Kalman filter method, based on the reported results in the literature.     

基于经验模态分解方法的拉曼光谱信号处理研究

经验模态分解(EMD)方法是一个以信号内在物理频率成分为对象的自适应时频分析方法,而常见的非平稳信号分析方法,比如小波分析,它需要选择小波基,不同小波基的分析结果不同;拉曼光谱信号是典型的非线性和非平稳信号,EMD方法充分地保留了信号本身的非线性和非平稳的特征,适应于拉曼光谱信号的分析。实验在自行研制的拉曼光谱测试平台上获得了原始的拉曼光谱信号,并通过经验模态分解将信号分解成不同频率的10个本征模式分量,信号能量集中在750cm^-1和1500cm^-1左右,最后进行了频率成分分析和去噪处理,并和小波分析方法进行了对比,验证了EMD方法的有效性和实用性,该方法在拉曼光谱信号分析中有较好的应用前景。     

冶金轧钢厂的谐波治理

利用中间谐波分析方法，准确地分析出马钢两个轧钢厂的谐波结构情况。在此基础上重新设计了滤波器参数，按照尽可能利用原滤波元件，降低改造费用的原则，对设计参数作进一步优化，改造后的滤波器投运两年多，获得成功。从而证明，利用中间谐波分析方法，治理轧钢厂电能质量，是一种国内先进的方法。     

基于自适应数字滤波的旋转机械动平衡边缘计算

为了提高机械设备不平衡故障的判断准确率,针对目前振动信号检测分析计算均在服务器云平台进行的现状,设计一种在边缘计算端实现的方式.通过自适应数字滤波方法分析出旋转机械不平衡故障,利用中心频率自适应带通数字滤波器实现噪声去除,并且将算法固化到嵌入式单片机上.通过中心频率带通滤波器,利用数字化滤波器传递函数,对采集的信号数据...     

A double laser filtering approach to vibration noise rejection for hot-rolled strip flatness measurement

This paper proposes a new filtering method based on the Kalman filtering algorithm for hot-rolled strip flatness measurement system. The system involves processing slowly changing signal, which can be considered as a bounded random process, and its model parameters are completely unknown. The noise rejection strategy in double lasers can generate a compensation signal. Since the initial and accumulative error would lead to negative filter effect or even cause divergence, Kalman filter is integrated to effectively deal with the initial error and enhance convergence. In this setting, the noise rejection strategy is used as a prediction model to constitute a similar Kalman filter. The correlated error caused by measurement error is coped with by a compensation model based on the feature of correlated error to enhance the filter effect. Both theoretical analysis and simulations show that the new algorithm has a better filter effect than the traditional Kalman filtering algorithm for the system.     

Defining Triangular Probability Distributions from Historical Cost Data

During the development of an automated cost estimating system, several factors led to the selection of the triangular probability-density function to model historical construction costs. The triangular-density function is customarily used when function parameters are directly estimated by experts. A typical example is for estimating activity durations by identifying a minimum value, a most likely value, and a maximum value. These values are then used to construct triangular-density functions to represent uncertain activity durations. For this work, however, it was necessary to estimate parameters of the triangular-density function using historical cost data. A methodology was developed to generate test data and compare three methods of parameter estimation—maximum likelihood, moment matching, and least-squares curve-fitting techniques. It is concluded that optimized moment matching and least-squares techniques produce more accurate parameter estimates, while maximum likelihood estimation yields less accurate results. It is further concluded that the least-squares minimization method always performed as well as or better than the optimized moment matching technique and was therefore selected as the method of choice for the project.     

Forecasting of Reference Evapotranspiration by Artificial Neural Networks

In recent years, artificial neural networks (ANNs) have been applied to forecasting in many areas of engineering. In this note, a sequentially adaptive radial basis function network is applied to the forecasting of reference evapotranspiration (ETo). The sequential adaptation of parameters and structure is achieved using an extended Kalman filter. The criterion for network growing is obtained from the Kalman filter’s consistency test, while the criteria for neuron/connection pruning are based on the statistical parameter significance test. The weather parameter data (air temperature, relative humidity, wind speed, and sunshine) were available at Nis, Serbia and Montenegro, from January 1977 to December 1996. The monthly reference evapotranspiration data were obtained by the Penman-Monteith method, which is proposed as the sole standard method for the computation of reference evapotranspiration. The network learned to forecast ETo,t+1 based on ETo,t?11 and ETo,t?23. The results show that ANNs can be used for forecasting reference evapotranspiration with high reliability.     

基于红外热成像原理的嵌入式下渣检测方法

通过对现有转炉下渣检测系统的分析,提出了一种基于红外热成像原理的嵌入式下渣检测方法,介绍了红外热成像技术原理,阐述了系统嵌入式架构及具体实现方法。该方法通过红外热像仪采集连续钢流图像,结合嵌入式系统技术,利用数字信号处理器(DSP)对采集到的钢流图像数据根据钢水与钢渣在远红外区的热辐射率不同进行特征信号提取与处理,再经DSP的主机并行接口(HPI)将处理后的图像数据发送给ARM处理器,最后采用图形用户接口MiniGUI设计了嵌入式环境下的图形用户界面,实现对转炉出钢过程中钢流状态的实时监控。现场试验表明:该方法成本低,对现有设备改造小,提高了挡渣效果,较好满足了钢水炉外精炼的要求。     

Time-Expanded Sampling for Ensemble-Based Filters: Assimilation Experiments with Real Radar Observations

By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time,the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and,hence,can reduce the computational cost of an ensemble-based filter.In this study,this approach is tested for the first time with real radar data from a tornadic thunderstorm.In particular,four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemblebased filters.In these experiments,the ensemble square-root filter (EnSRF) was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs,respectively,and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances.The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis,especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation.These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.     

A placebo-controlled dose-ranging study of lansoprazole in the management of reflux esophagitis

Various signal processing techniques have been proposed to improve spectral estimation of closely spaced sinusoids in the presence of noise. This paper exploits frequency prior knowledge information to extract single peaks in magnetic resonance spectra, corresponding to metabolites of interest, by means of a highly selective finite impulse response filter. Thereafter the estimation of the parameters of the peaks is carried out using a singular-value-decomposition-based method known as HTLS. The new technique improves the performance of fully automated magnetic resonance spectroscopy data quantification when frequency prior knowledge is available.     

Estimating multiple temporal mechanisms in human vision

When studying human ability to perceive temporal changes in luminance it is customary to estimate either temporal impulse response shapes or temporal modulation transfer functions, the representation of the impulse response in the frequency domain. The advantages and limitations of previous methods are summarized. We then describe an approach based on use of an impulse response basis set that resolves some of those limitations. We next present psychophysical results for spatiotemporal signal detection in spatiotemporal noise, together with an economical model of performance. The model is based on accepted notions of psychophysical detection mechanisms and the filter basis set described in the first part of the paper. The best-fitting model requires only eight parameters, as opposed to the 198 parameters required to separately fit each psychometric function, and captures both qualitative and quantitative properties of the psychophysical data. Finally, the best-fitting model indicates that only two temporal filters are necessary to describe the performance of each of three subjects under the specific stimulus conditions employed here.     

相干平均在刚性转子单面动平衡中的应用

阐述了用影响系数法做现场动平衡的基本原理及其计算方法 ,指出常规的带通方法对动平衡振动信号处理后确定的振幅和相位往往是不稳定的 ,同时提出了用相干平均的办法解决该问题。理论分析和现场实践均表明 ,这一方法是非常有效的。     

基于小波包理论的爆破振动信号能量分析研究

爆破振动信号是一种极为复杂的非平稳信号,具有持时短、突变快的特点,本文结合实际爆破监测数据,利用小波包变化提取信号的频带能量分布特征,对爆破振动信号中不同频带的能量特征进行了分析研究。研究结果表明:爆破振动信号能量绝大部分集中在0～200Hz,在这一频带根据爆破条件不同其能量又分布于不同子频带。随着爆破药量、爆破地震波传播距离的增大,低频带所占能量不断增加。因此该方法对爆破地震波传播及破坏机理,以及爆破降振研究是一种有效的方法。     

Hearing levels and age in cleft palate patients

Automatic long-term vigilance analysis systems require information about the occurrence and type of eye movements, in addition to information about other physiological signals. This paper presents a method to detect different types of eye movements in ambulatory recordings. The method is based on the application of a weighted FIR-median-hybrid filter in the preprocessing of the signal and on the novel use of linear correlation between two EOG signals which are obtained using a new, improved electrode montage. The evaluation of the method showed that it performed well in detecting isolated unambiguous eye movements, but differences were observed in comparison to visual scoring in borderline cases. The method was found to be suitable for use as part of a signal analysis system for drowsiness studies.     

Bayesian State Estimation Method for Nonlinear Systems and Its Application to Recorded Seismic Response

The focus of this paper is to demonstrate the application of a recently developed Bayesian state estimation method to the recorded seismic response of a building and to discuss the issue of model selection. The method, known as the particle filter, is based on stochastic simulation. Unlike the well-known extended Kalman filter, it is applicable to highly nonlinear systems with non-Gaussian uncertainties. The particle filter is applied to strong motion data recorded in the 1994 Northridge earthquake in a seven-story hotel whose structural system consists of nonductile reinforced-concrete moment frames, two of which were severely damaged during the earthquake. We address the issue of model selection. Two identification models are proposed: a time-varying linear model and a simplified time-varying nonlinear degradation model. The latter is derived from a nonlinear finite-element model of the building previously developed at Caltech. For the former model, the resulting performance is poor since the parameters need to vary significantly with time in order to capture the structural degradation of the building during the earthquake. The latter model performs better because it is able to characterize this degradation to a certain extent even with its parameters fixed. For this case study, the particle filter provides consistent state and parameter estimates, in contrast to the extended Kalman filter, which provides inconsistent estimates. It is concluded that for a state estimation procedure to be successful, at least two factors are essential: an appropriate estimation algorithm and a suitable identification model.     

基于颗粒流程序的非定常西原体模型

为实现岩石试样蠕变全过程的准确模拟,并从细观角度探究蠕变过程中微裂隙的发生和发展规律,在二维颗粒流程序(PFC2D)中开发出具有黏弹塑性特征的西原体流变接触本构模型,进一步提出包含两种非定常元件的非定常西原体模型,推导了模型本构关系和蠕变方程.在PFC2D中调用自定义西原体流变模型,通过参数调试,获得与真实试样具有相同强度特性的数值试样.以室内单轴压缩蠕变试验数据为基础,在Matlab中对模型非定常参数进行拟合反演分析.在此基础上,进行单轴压缩蠕变试验的模拟,计算过程中分别采用定常和非定常两种模型,并对微裂隙进行监测.对比分析结果表明:定常模型仅适用于衰减和稳定蠕变阶段;非定常模型也可用于描述加速蠕变阶段,从而准确模拟蠕变全过程;加速蠕变阶段主要是由微裂隙的加速发展而产生,加速蠕变将导致试样剪切破坏.      

Despiking Acoustic Doppler Velocimeter Data

A new method for detecting spikes in acoustic Doppler velocimeter data sequences is suggested. The method combines three concepts: (1) that differentiation enhances the high frequency portion of a signal, (2) that the expected maximum of a random series is given by the Universal threshold, and (3) that good data cluster in a dense cloud in phase space or Poincaré maps. These concepts are used to construct an ellipsoid in three-dimensional phase space, then points lying outside the ellipsoid are designated as spikes. The new method is shown to have superior performance to various other methods and it has the added advantage that it requires no parameters. Several methods for replacing sequences of spurious data are presented. A polynomial fitted to good data on either side of the spike event, then interpolated across the event, is preferred by the authors.     

Spatio-temporal EEG source localization using simulated annealing

The estimation of multiple dipole parameters in spatio-temporal source modeling (STSM) of electroencephalographic (EEG) data is a difficult nonlinear optimization problem due to multiple local minima in the cost function. A straightforward iterative optimization approach to such a problem is very susceptible to being trapped in a local minimum, thereby resulting in incorrect estimates of the dipole parameters. In this paper, we present and evaluate a more robust optimization approach based on the simulated annealing algorithm. The complexity of this approach for the STSM problem was reduced by separating the dipole parameters into linear (moment) and nonlinear (location) components. The effectiveness of the proposed method and its superiority over the traditional nonlinear simplex technique in escaping local minima were tested and demonstrated through computer simulations. The annealing algorithm and its implementation for multidipole estimation are also discussed. We found the simulated annealing approach to be 7-31% more effective than the simplex method at converging to the true global minimum for a number of different kinds of three-dipole problems simulated in this work. In addition, the computational cost of the proposed approach was only marginally higher than its simplex counterpart. The annealing method also yielded similar solutions irrespective of the initial guesses used. The proposed simulated annealing method is an attractive alternative to the simplex method that is currently more common in dipole estimation applications.     

Simplified Cone Penetration Test-based Method for Evaluating Liquefaction Resistance of Soils

This paper presents a new simplified method for assessing the liquefaction resistance of soils based on the cone penetration test (CPT). A relatively large database consisting of CPT measurements and field liquefaction performance observations of historical earthquakes is analyzed. This database is first used to train an artificial neural network for predicting the occurrence and nonoccurrence of liquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to generate a set of artificial data points that collectively define the liquefaction boundary surface, the limit state function. An empirical equation is further obtained by regression analysis to approximate the unknown limit state function. The empirical equation developed represents a deterministic method for assessing liquefaction resistance using the CPT. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the Bayesian mapping function approach. The results of the probabilistic analyses, expressed as a mapping function, provide a simple means for probability-based evaluation of the liquefaction potential. The newly developed simplified method compares favorably to a widely used existing method.