基于IEEE 1500标准的IP核测试壳设计

随着集成电路规模的不断扩大,基于IP核复用的SOC设计技术被广泛应用,但是由于IP核的来源不同,设计标准的不兼容等因素,使得SOC的测试变得越来越困难。IEEE1500标准设立的目标是标准化IP核提供商与用户之间的测试接口,简化核测试信息的复用。本文在研究IEEE1500标准的硬件结构基础上,讨论了1500的测试指令集,然后以基准电路集ISCAS89中的s349时序电路为例,对其进行全扫描设计之后,详细说明了基于IEEE1500标准的IP核测试壳各部分的设计过程,最后通过仿真实验,验证了在不同测试指令和故障模式下,测试壳的有效性。     

基于FPGA的智能火工品等效器设计实现

针对导弹弹上火工品发射前检测问题,设计一种基于FPGA的智能火工品等效器。该系统采用EP3C16F256C8以及其外围电路,在火工品通路测试(低压状态)时等效火工品电爆管阻值;在低压时序测试、高压时序测试时,检测时序指令发出情况。对等效器等效通路进行电阻值测试,同时在实验测试平台对低压电流时序以及高压电压时序进行实验验证,结果表明,本等效器其电阻值、时序宽度满足设计要求并具有高可靠性、良好维修性、实用性强等特点,可以广泛推广和应用。     

A coupled power-voltage equilibrium strategy based on droop control for fuel cell/battery/supercapacitor hybrid tramway

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources,achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.     

Fuzzy modeling and particle swarm optimization for determining the optimal operating parameters to enhance the bio-methanol production from sugar cane bagasse

This work aims to maximize the production of bio-methanol from sugar cane bagasse through pyrolysis. The maximum value of the bio-methanol yield can be obtained as soon as the optimal operating parameters in a pyrolysis batch reactor are well defined. Using the experimental data, the fuzzy logic technique is used to build a robust model that describes the yield of bio-methanol production. Then, Particle Swarm Optimization (PSO) algorithm is utilized to estimate the optimal values of the operating parameters that maximize the bio-methanol yield. Three different operating parameters influence the yield of bio-methanol from sugar cane bagasse through pyrolysis. The controlling parameters are considered as the reaction temperature (°C), reaction time (min), and nitrogen flow (L/min). Accordingly, during the optimization process, these parameters are used as the decision variables set for the PSO optimizer in order to maximize the yield of bio-methanol, which is considered as a cost function. The results demonstrated a well-fitting between the fuzzy model and the experimental data compared with previous predictions obtained by an artificial neural network (ANN) model. The mean square errors of the model predictions are 0.11858 and 0.0259, respectively, for the ANN and fuzzy-based models, indicating that fuzzy modeling increased the prediction accuracy to 78.16% compared with ANN. Based on the built model, the PSO optimizer accomplished a substantial improvement in the yield of bio-methanol by 20% compared to that obtained experimentally, without changing system design or the materials used.     

An adaptive Tikhonov regularization parameter choice method for electrical resistance tomography

Electrical resistance tomography (ERT) reconstructs the conductivity distribution from the boundary changes of electrical measurements. The inverse problem of ERT is seriously ill-posed where regularization methods are needed to treat this ill-posedness. A proper choice of regularization parameter which controls the degree of smoothing is very important for these regularization methods. Although have been a variety of methods, such as L-curve method, to choose a reasonable parameter for the problem, these methods usually result in a scalar parameter which cannot distinctly express the spatial characteristic of the conductivity distribution. So a spatially adaptive regularization parameter choice method is proposed for regularizing the inverse problem of ERT based on Tikhonov regularization. Since large regularization parameters can stabilize and smoothen the solution, while small regularization parameters can approximate and sharpen the solution, the proposed method adaptively updates the regularization parameters during the iteration process and provides spatially varying parameter for each pixel of the reconstructed image. When the iteration is stopped, large regularization parameters for the smooth background region and small regularization parameters for the object region can be obtained. The method is discussed using simulated data for some typical conductivity distributions, and further applied to the analysis of real measurement data acquiring from the practical system. The results demonstrate that flexible regularization parameter vectors can be achieved for different distributions and the strength of regularization is adaptively provided for different regions in a specific distribution. The adaptive method achieves an efficient and reliable regularization solution and has outstanding performance in noise immunity especially in smooth background regions.     

微惯性测量器件的标定方法研究

在捷联惯性航向姿态测量系统中,微惯性器件是核心部分,陀螺和加速度计的精度直接影响整个系统的精度.详细给出了惯性测量器件的标定方法,利用软件来补偿器件的误差,从而改善系统性能.     

基于VB的数据挖掘应用

首先介绍了数据挖掘的过程,然后提出使用VB以及ADO开发数据挖掘应用的一般方法,并通过一个实际应用问题, 展示了方法的具体实现.这种方法便于使用,是实现数据挖掘的良好工具.     

一种直流电机伺服系统的μ综合研究

分析了直流电机伺服系统中的不确定性，建立了直流电机伺服系统的不确定性模型，探讨了户综合控制算法在直流电机跟踪系统中的应用，并使用D-K递推方法进行了计算，给出了最后设计结果。使用Mtalab进行仿真实验比较，证明这种控制算法能够很好地满足系统需要的控制要求，且具有较强的鲁棒性。     

Human–robot interaction based on gesture and movement recognition

Human–robot interaction (HRI) has become a research hotspot in computer vision and robotics due to its wide application in human–computer interaction (HCI) domain. Based on the explored algorithms of gesture recognition and limb movement recognition in somatosensory interaction, an HRI model of a robotic arm is proposed for robot arm manipulation. More specifically, 3D SSD architecture is used for the location and identification of gesture and arm movement. Then, DTW template matching algorithm is adopted to trace the dynamic gestures. The interactive scenarios and interactive modes are designed for experiment and implementation. Virtual interactive experimental results have demonstrated the usefulness of our method.     

无线传感执行网络的协调机制研究*

主要研究了无线传感执行网络中执行节点之间的协调,提出了基于单执行节点任务的分布式协调机制。在多执行节点协调算法中,建立了多执行节点协调的数学模型,引入基于进化算法的多目标优化,提高了系统的最优性能。