基于DSP智能体的控制与实现

传统基于单片机的智能体在控制性能和指令响应速度上都受到一定限制,为提高智能体的控制性能和快速反应能力,研究实现了基于DSP的智能体;首先,对该智能体从运动学角度进行系统建模,提供理论依据,通过模型计算,可以获得精确的控制数据;然后,分析了智能体的基本动作和环境状态,并用智能语言进行描述,最后,分别实现DSP控制子系统、无线通讯子系统、音乐子系统和智能体车身子系统,从而实现了高速无线控制的多功能智能体;实验表明,该智能体线运动精度为0.12cm,最高速度为2.92m/s,可快速精确定位。     

基于图像检测的发动机缸体探伤系统设计及应用

为了实现某型号航空发动机缸体的自动化检测,设计了一套全自动荧光磁粉探伤系统。介绍了系统的结构和实现方式、重点介绍了图像采集和图像处理部分,系统采用Laplacian算子对原始图像进行锐化处理,然后采用Prewitt算子进行边缘提取,最后采用面积和周长两个物理量作为判断产品合格与否的特征值;实际测量显示,系统的测量精度可达0.01 mm,满足发动机缸体检测的要求。     

基于TDOA技术的自适应定位系统研究

分析了现有基于TDOA测距技术的无线传感器网络定位系统;针对因锚节点移动而造成的锚节点位置信息失效问题,提出锚节点自适应状态转换机制,即时更新锚节点的位置信息;并针对由于可用锚节点数量不足而造成的非三边定位问题,给出了基于邻居锚节点位置信息的解决方法;最后在Cricket室内定位系统中引入并实现了方案,实验证明该方案可以有效地解决此类问题,具有一定的应用意义。     

Tokamak等离子体图像诊断系统的研制

针对Tokamak等离子体放电实验中需要对等离子体进行直观诊断的需求,根据实验的特点,研制了等离子体图像诊断系统,该系统以Matrox公司的Meteor Ⅱ/Digital采集卡和UNIQ VISION公司的UC610相机等为硬件核心,采用了Visual C++多线程技术进行实时图像采集,采用了Bayer变换和Gamma校正等数字图像处理技术将采集到的Bayer格式的灰度数字图像转换为彩色数字图像;该图像诊断系统实现了Tokamak放电实验中等离子体图像实时采集、处理和诊断等功能,充分满足了等离子体放电实验诊断的要求。     

基于RTX的复杂虚拟试验分层实时网络环境研究

复杂实时仿真系统中不同层次对实时性、可靠性要求各不相同;网络和操作系统是该类系统环境的重要组成部分;针对硬件在回路试验的实时需求,提出了基于RTX下的反射内存网的半实物接入网络,构建了基于RT-TCP/IP的虚拟试验局域网;其操作系统层面,设计为弱实时任务在Windows内核上运行,而强实时任务分布在RTX内核之上;文中对各层面的实时性进行了测试,分析了层面间的实时性约束;结合某飞行试验系统的虚拟试验,给出了具体的设计方案,满足了应用中不同实时性的要求。     

基于改进遗传算法的RBF网络的截球策略

在RoboCup2D仿真足球比赛中,球员的底层动作设计的好坏直接影响着比赛的输赢,特别是一些关键的动作,比如截球、传球、射门等动作。鉴于此,提出一种新的截球方法,即改进的遗传算法和RBF神经网络相结合的截球方法。该方法是用改进的遗传算法优化RBF神经网络的结构参数,通过优化,提高了网络的全局搜索效率。实验表明,经过改进遗传算法优化的RBF神经网络的截球成功率比单一的RBF神经网络截球成功率高很多。     

Matching pursuit based on nonparametric waveform estimation

Matching pursuit (MP) extracts signal feature components by decomposing the observed signal into a linear expansion of waveforms that are selected from a redundant dictionary of basis functions. It is difficult to predefine a parametric basis function that contains all prior information about the observed signal in practice, which restricted the application of MP. Focusing on this defect of MP, we present a modified algorithm of MP which decomposes the observed signal into a series combinations of waveforms, these waveforms are calculated by the nonparametric waveform estimation (NWE) method and used to best match the signal local structures. As a result, it is not needed to predefine the parametric basis function. With the NWE method, the adaptive adjustment of template signals makes it unnecessary for the method to require priori information, so that in practical applications it has better flexibility and adaptability. The extraction results of simulation signals are compared with the traditional MP decomposition, thus verifying the function of the proposed method. The extraction of testing signals on the rotor rig has again verified the feasibility and effectiveness of the method.     

Adaptive integral method combined with the loose GMRES algorithm for planar structures analysis

In this article, the adaptive integral method (AIM) is used to analyze large‐scale planar structures. Discretization of the corresponding integral equations by method of moment (MoM) with Rao‐Wilton‐Glisson (RWG) basis functions can model arbitrarily shaped planar structures, but usually leads to a fully populated matrix. AIM could map these basis functions onto a rectangular grid, where the Toeplitz property of the Green's function would be utilized, which enables the calculation of the matrix‐vector multiplication by use of the fast Fourier transform (FFT) technique. It reduces the memory requirement from O(N²) to O(N) and the operation complexity from O(N²) to O(N log N), where N is the number of unknowns. The resultant equations are then solved by the loose generalized minimal residual method (LGMRES) to accelerate iteration, which converges much faster than the conventional conjugate gradient method (CG). Furthermore, several preconditioning techniques are employed to enhance the computational efficiency of the LGMRES. Some typical microstrip circuits and microstrip antenna array are analyzed and numerical results show that the preconditioned LGMRES can converge much faster than conventional LGMRES. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

Broadcasting scheme with low client buffers and bandwidths for video-on-demand applications

Efficient data broadcasting is independent of request arrivals, and is thus highly promising when transmitting popular videos. A conventionally adopted broadcasting method is periodic broadcasting, which divides a popular video into segments, which are then simultaneously broadcast on different data channels. Once clients want to watch the video, they download the segments from these channels. The skyscraper broadcasting (SkB) scheme supports clients with small bandwidths. An SkB client requires only two-channel bandwidths to receive video segments. This work proposes a reverse SkB (RSkB) scheme, which extends SkB by reducing buffering spaces. The RSkB is mathematically shown to achieve on-time video delivery and two-channel client bandwidths. A formula for determining the maximum number of segments buffered by an RSkB client is presented. Finally, an analysis of RSkB reveals that its client buffer requirements are usually 25–37% lower than SkB. Extensive simulations of RSkB further demonstrate that RSkB yields lower client buffer demand than other proposed systems.