循环流化床稀相区对流换热的理论分析和实验研究

对循环流化床上部稀相区气固混合物横掠圆管的对流换热研究,多数是针对鼓泡床的研究,而对循环流化床上部稀相区的对流换热研究目前还很少。本文对稀相含尘气流横向冲刷圆管的对流换热进行了研究,并在理论分析的基础上,在热态循环流化床实验台的上部稀相区进行了实验。采用平均粒径分别为137μm,146μm和326μm的石英砂为床料。实验结果表明,稀相含尘气流与纯空气横掠圆管时的对流换热系数之比hd/hg主要受稀相含尘气流密度和颗粒粒径的影响,通过理论分析和实验数据的拟合,得到稀相含尘气流横掠圆管的准则方程。研究基于热态实验,结果更接近于实际工况,可为循环流化床的设计提供理论依据。     

阵列信号维纳滤波用于主动声呐图像增强处理

声呐图像的噪声背景抑制是提高水下目标检测能力的重要问题。针对声呐图像背景斑点噪声强、目标轮廓模糊、目标回波对比度低等问题,利用确定性目标回波信号与随机分布的干扰噪声之间的相关统计特性差异,采用基于最小均方差准则的阵列信号维纳滤波器,通过主动最小方差无畸变响应（Minimum Variance Distortionless Response,MVDR）波束形成和后置维纳滤波的两级处理,去除声呐随机噪声背景。试验数据的处理结果表明：在噪声干扰条件下,相比于常规波束形成（Common Beamforming,CBF）,主动MVDR处理提高了目标回波的局部信噪比,后置维纳滤波处理降低了随机分布的斑点噪声,使声呐图像的清晰度得到增强。     

两种机炉协调控制系统特性的分析比较

根据两种机炉协调控制策略——CBF和CTF的实际应用情况,从单元机组控制对象的动态特性出发,对其特点进行分析、比较,阐述了两种协调控制策略的控制品质特性,可为机炉协调控制系统的完善提供参考。     

Automatic selection of arterial input function on dynamic contrast-enhanced MR images

Dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) data analysis requires the knowledge of the arterial input function (AIF) to quantify the cerebral blood flow (CBF), volume (CBV) and the mean transit time (MTT). AIF can be obtained either manually or using automatic algorithms. We present a method to derive the AIF on the middle cerebral artery (MCA). The algorithm draws a region of interest (ROI) where the MCA is located. Then, it uses a recursive cluster analysis on the ROI to select the arterial voxels. The algorithm had been compared on simulated data to literature state of art automatic algorithms and on clinical data to the manual procedure. On in silico data, our method allows to reconstruct the true AIF and it is less affected by partial volume effect bias than the other methods. In clinical data, automatic AIF provides CBF and MTT maps with a greater contrast level compared to manual AIF ones. Therefore, AIF obtained with the proposed method improves the estimate reliability and provides a quantitatively reliable physiological picture.     

用于脑血流量检测的近红外光谱术

介绍了用于大脑血流量检测的近红外光谱术的基本原理和实验体系,该系统可完成对近红外光学信号的实时采集、处理和显示等功能。在血模型实验结果基础上,报道了大脑血流量变化的近红外光学检测结果。     

Fast computation of wideband RCS using characteristic basis function method and asymptotic waveform evaluation technique

The Asymptotic Waveform Evaluation (AWE) technique is an extrapolation method that provides a reduced-order model of linear system and has already been successfully used to analyze wideband electromagnetic scattering problems. As the number of unknowns increases, the size of Method Of Moments (MOM) impedance matrix grows very rapidly, so it is a prohibitive task for the computation of wideband Radar Cross Section (RCS) from electrically large object or multi-objects using the traditional AWE technique that needs to solve directly matrix inversion. In this paper, an AWE technique based on the Characteristic Basis Function (CBF) method, which can reduce the matrix size to a manageable size for direct matrix inversion, is proposed to analyze electromagnetic scattering from multi-objects over a given frequency band. Numerical examples are presented to illustrate the computational accuracy and efficiency of the proposed method.     

基于LRU和扩展CBF的网络大流检测

高速网络流量检测中的大流检测已成为当前一种重要的、高效准确的可扩展流量测量机制,针对CBF（Count Bloom Filter）容易溢出的问题,将扩展的CBF应用于流量测量,防止过滤器溢出,并且结合LRU链表存储机制,共同应用于网络大流检测之中。经理论分析,所研究的流量测量算法LRU_MCBF（Least Recently Used_Multiple Count Bloom Filter）占用空间小,时间复杂度低;通过仿真实验验证了LRU_MCBF在大流测量中漏报率和错报率较低,能实现高速网络环境下大流对象的准确提取。     

水声阵列信号处理对角减载技术

针对独立高斯白噪声背景和多个平面波干扰,尤其是低输入信噪比的情况,提出一种基于阵列信号协方差矩阵对角减载的波束形成技术。通过足够多次快拍的估计,得到接收信号稳定的协方差矩阵,对协方差矩阵进行适量的对角减载能提高阵列输出增益以及多目标的分辨能力。对基于对角减载的常规波束形成和最小方差无畸变波束形成器的阵列增益进行了仿真,分析了阵列增益随减载系数的变化关系,并研究了多目标分辨时对角减载系数的取值区间,最后仿真验证了对角减载技术提高MVDR多目标分辨能力的有效性。