基于燃烧模型的微弱火焰高度检测

火焰高度是描述火焰特性、确定火焰燃烧状态的重要参数,目前多使用目测方法进行检测.微弱火焰具有亮度低、信噪比低、火焰轮廓模糊的特点,人工目测困难,常规图像分析方法检测对阈值依赖性高.为解决上述问题,在利用常规图像处理方法提取的不完整火焰边缘后,建立火焰轮廓的多参数模型,进而计算火焰高度.实验结果表明:该算法抗干扰能力强,...     

Turbulent flow computations on a hybrid cartesian point distribution using meshless solver LSFD-U

This paper may be considered as a sequel to one of our earlier works pertaining to the development of an upwind algorithm for meshless solvers. While the earlier work dealt with the development of an inviscid solution procedure, the present work focuses on its extension to viscous flows. A robust viscous discretization strategy is chosen based on positivity of a discrete Laplacian. This work projects meshless solver as a viable cartesian grid methodology. The point distribution required for the meshless solver is obtained from a hybrid cartesian gridding strategy. Particularly considering the importance of an hybrid cartesian mesh for RANS computations, the difficulties encountered in a conventional least squares based discretization strategy are highlighted. In this context, importance of discretization strategies which exploit the local structure in the grid is presented, along with a suitable point sorting strategy. Of particular interest is the proposed discretization strategies (both inviscid and viscous) within the structured grid block; a rotated update for the inviscid part and a Green-Gauss procedure based positive update for the viscous part. Both these procedures conveniently avoid the ill-conditioning associated with a conventional least squares procedure in the critical region of structured grid block. The robustness and accuracy of such a strategy is demonstrated on a number of standard test cases including a case of a multi-element airfoil. The computational efficiency of the proposed meshless solver is also demonstrated.     

Spectral analysis of turbulence based on the DNS of a channel flow

The development and assessment of spectral turbulence models requires knowledge of the spectral turbulent kinetic energy distribution as well as an understanding of the terms which determine the energy distribution in physical and wave number space. Direct numerical simulation (DNS) of turbulent channel flow yields numerical “data” that can be, and was, analyzed using a spatial Fast Fourier Transform (FFT) to obtain the various spectral turbulent kinetic energy balance terms, including the production, dissipation, diffusion, and the non-linear convective transfer terms.     

基于电容传感器的电容近炸引信炸高散布研究

基于电容近炸引信的探测场区为准静电场,根据准静电场的分布特征,类比无线电引信的方向函数,建立电容引信的场强分布函数,得到电容近炸引信的等场强探测方向图近似为一个长短半轴相差20％的椭球,验证了电容近炸引信在不同弹目交会条件下炸高散布小的结论.     

Thermal dispersion effects on non-Darcy convection over a cone

The similarity solution for non-Darcy mixed convection about an isothermal vertical cone with fixed apex half angle, pointing downwards in a fluid saturated porous medium with uniform free stream velocity is obtained. The effect of thermal dispersion is studied in both the aiding and opposing flows. Flow separation is observed when the forced and free convection act in opposite directions. It is interesting to note that when buoyancy effects are neglected, the similarity solution exists for all realistic power law variations of the wall temperature, and for uniform free stream velocity, a closed form solution is possible for the isothermal wall temperature and uniform free stream. The heat transfer is enhanced due to the thermal dispersion effects.     

基于自组织神经网络的炉膛火焰燃烧诊断系统

针对目前大型锅炉火焰检测手段的落后现状,提出了一种基于数字图像处理与自组织竞争神经网络进行燃烧诊断的方法,设计了一套火焰燃烧诊断系统.利用数字图像处理技术提取火焰特征量,应用神经网络的竞争学习对不同负荷下的全炉膛火焰图像进行识别分类,从而实现燃烧诊断和灭火预警的功能.     

基于ICA方法的朴素贝叶斯分类器

朴素贝叶斯分类器是一种简单而高效的分类器,但需要属性独立性假设,无法表示现实世界中属性之间的依赖关系,影响了其分类性能.利用独立分量分析提升朴素贝叶斯分类性能,把样本投影到由独立分量所确定的特征空间,提高了朴素贝叶斯分类器的分类性能.实验结果表明,这种基于独立分量分析的朴素贝叶斯分类器具有良好的性能.     

Platoon dispersion prediction under the condition of adjacent cycle traffic flow overlapping based on Support Vector Regression

Coordinated signal control can improve the continuity of vehicular traffic flow movement and reduce delay. Cycle Flow Profile is the base for calculating coordinated signal control parameters. Platoon dispersion characteristic determines the Cycle Flow Profile. So, improving platoon dispersion prediction accuracy can obtain significant benefit for signal coordination. When the velocities of the vehicles vary greatly, faster vehicles of next cycle can catch up the slower vehicles of the current cycle. Traffic flow overlapping of adjacent cycle is an important characteristic. Support Vector Regression is adopted to predict platoon dispersion and compares prediction accuracy with Robertson formula. The results are encouraging; Support Vector Regression has higher prediction accuracy.     

基于缸压高频ARMA模型的爆震识别方法

研究以汽油机燃烧测试平台为基础,通过调整点火提前角以获得较大的爆震强度,并获得实验分析数据.选择低通燃烧压力信号峰值前10°后20°曲轴转角范围最做为爆震窗口.对随机选择的一系列爆震窗口燃烧压力高频振动信号构建时间序列模型,并以模型参数向量均值的马氏距离为爆震识别标识.用蒙特-卡罗法对非爆震工况序列马氏距离进行选择,获得爆震阈值.并通过工程上广泛使用的VDO算法验证这种爆震识别方法的可行性.     

基于文丘里流量传感器的湿气两相流量模型研究

研究旨在通过计算流体动力学(CFD)仿真技术预测的湿气气、液两相流量.以双差压长喉颈文丘里流量传感器为测量手段.模拟压力范围0.4,0.6,0.8,1.0,1.2 MPa,气相体积流量范围为140～283 m3/h,温度范围23 ～30℃,含液率范围0.5％～1.5％.文丘里流量传感器口径为DN100,节流比为0.55.多相流模型采用离散相模型(DPM),利用欧拉壁面(EWF)模型以模拟管壁上的薄液膜.分析得出压力、气相流速和液相体积含率(LVF)对液膜厚度的影响规律.根据仿真结果建立基于双差压比值法的气、液两相流量预测模型.将仿真值与实验值进行比较,气相流量模型预测的均方根误差为1.8％,且液相流量模型预测的均方根误差为6.1％.     

基于改进神经网络的洪水预报模型研究

人工神经网络作为一种非常优越的非线性函数逼近方法已经被广泛应用。采用时间序列分析选择输入因子,并提出一种直观可行的网络参数(隐层数和隐层节点数、训练次数)确定方法。通过对模型的仿真测试,有效地提高了模型预报精度。     

基于观测数据的数学模型预测性检验理论

基于显著性检验的意义及其存在的问题,提出了评价经验模型预测性的观点与方法,从理论与实践两方面探讨有关的统计检验手段,进而提出预测性检验理论.所涉方法用于化工装置的建模实践,实际效果良好.在其他领域,同样具有理论和实践的指导意义.     

基于Ontology的语义信息检索模型研究

在信息检索过程中引入语义,可以大大提高信息检索准确度,其中Ontology扮演了重要的角色.基于Ontology研究了语义信息检索原理、体系结构及其模型实现的关键技术,设计并实现了基于Ontology的信息检索系统原型,对研究进行了验证.实验结果表明,基于Ontology的检索大大提高了信息的查准率和查全率.     

Analysis and approximation of a fractional Laplacian-based closure model for turbulent flows and its connection to Richardson pair dispersion

We study a turbulence closure model in which the fractional Laplacian ${(?\Delta )}^{\alpha }$ of the velocity field represents the turbulence diffusivity. We investigate the energy spectrum of the model by applying Pao’s energy transfer theory. For the case $\alpha =1∕3$, the corresponding power law of the energy spectrum in the inertial range has a correction exponent on the regular Kolmogorov $?5∕3$ scaling exponent. For this case, this model represents Richardson’s particle pair-distance superdiffusion of a fully developed homogeneous turbulent flow as well as Lévy jumps that lead to the superdiffusion. For other values of $\alpha$, the power law of the energy spectrum is consistent with the regular Kolmogorov $?5∕3$ scaling exponent. We also propose and study a modular time-stepping algorithm in semi-discretized form. The algorithm is minimally intrusive to a given legacy code for solving Navier–Stokes equations by decoupling the local part and nonlocal part of the equations for the unknowns. We prove the algorithm is first-order accurate and unconditionally stable. We also derive error estimates for full discretizations of the model which, in addition to the time stepping algorithm, involves a finite element spatial discretization and a domain truncation approximation to the range of the fractional Laplacian.     

Investigation on the spatial-polarizational correlation based on 3GPP spatial channel model

The correlation among signals arriving at diferent elements of the antenna array has a significant impact on the performance of multiple-input multiple-output(MIMO)system.To investigate the inter-element correlation when slant polarized antennas are used,a general approach for calculating the correlation coefcient is proposed based on a model that incorporates the antenna configuration,namely the antenna spacing and the slant angle,as well as the channel parameters,such as the power azimuth spectrum(PAS)and the crosspolarization discrimination(XPD).By applying this method to the 3rd generation partnership project(3GPP)spatial channel model(SCM),the expression of the inter-element correlation when the PAS follows the Laplacian distribution is obtained.The approximate expressions are also given for two special cases,i.e.,the case where the angular spread(AS)of the PAS is small,and the case where the AS is so large that the PAS can be approximated by the uniform distribution.Using these expressions,the impact of the antenna configuration and the channel parameters on the correlation is analyzed.Following that,the trend of inter-element correlation with the slant angle is investigated.Finally,the equivalent relation between the slant angle and the antenna spacing is studied.The results can provide guidelines for the antenna configuration under diferent propagation conditions.     

A coarse-to-fine image registration method based on visual attention model

Image registration is fundamental and crucial to remote sensing. However getting highly accurate registration performance automatically and fast for large-field images consistently is a challenge. As a work around to this problem, we propose a new image registration concept based on visual attention in this paper. This concept employs the advantages of feature-based or area-based methods to improve the precision and efficiency of image registration. The key concept of proposed integrated scheme is to make optimum use of the highly prominent details in the full scene by means of visual attention computational mechanism. To testify the validation, comparisons with other classical methods are carried out on real-world images. The experimental results show that the proposed method can effectively perform on multi-view/multi-temporal remote sensing images with outstanding precision and time saving performance.     

基于相关系数和灰色模型的振荡序列预测

针对灰色模型在振荡序列预测中的不足,提出一种组合预测方法。针对时间序列,提出残差相关系数,计算当前训练数据和历史数据段的相关系数。在最相似历史数据段中利用遗传算法对灰色模型参数寻优,将该参数输入灰色模型实现当前预测。将当前预测结果和相似历史值加权求和,得到最终的预测结果。基于人工数据的对比实验结果表明,残差相关系数更能有效反映数据间的相似关系。基于天然气价格预测的对比实验结果表明,所提方法预测结果准确度更高。     

Human-robot communication based on a mind model

We propose a mental image directed semantic theory (MIDST) and apply it to integrated multimedia information understanding, such as cross-media operations through intermediate knowledge representation. This article describes a multiagent model of the human mind based on the MIDST and its application to human–robot communication. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

基于循环谱的数字信号的自动识别

介绍数字信号调制识别的谱相关法,在利用一些调制信号具有相同的功率谱密度时,它们的谱相关函数却有明显的区别。利用谱相关函数可以识别出低信噪比下的调制信号。通过循环谱中一些参数的提取,对高斯噪声中常见的数字通信信号的自动识别进行了计算机仿真。仿真结果表明,在信噪比不低于15 dB时,信号的平均识别率可以达到95%以上,有很好的实用前景。     

A change detection model based on neighborhood correlation image analysis and decision tree classification

This study introduces a change detection model based on Neighborhood Correlation Image (NCI) logic. It is based on the fact that the same geographic area (e.g., a 3 × 3 pixel window) on two dates of imagery will tend to be highly correlated if little change has occurred, and uncorrelated when change occurs. Computing the piecewise correlation between two data sets provides valuable information regarding the location and numeric change value derived using contextual information within the specified neighborhood. Various neighborhood configurations (i.e., multi-level NCIs) were explored in the study using high spatial resolution multispectral imagery: smaller neighborhood sizes provided some detailed change information (such as a new patios added to an existing building) at the cost of introducing some noise (such as changes in shadows). Larger neighborhood sizes were useful for removing this noise but introduced some inaccurate change information (such as removing some linear feature changes). When combined with image classification using a machine learning decision tree (C5.0), classifications based on multi-level NCIs yielded superior results (e.g., using a 3-pixel circular radius neighborhood had a Kappa of 0.94), compared to the classification that did not incorporate NCIs (Kappa = 0.86).