基于FPGA和ARM的弹上相位自动微调控制器设计与实现

为了提高相位自动微调控制器的控制性能,针对某型导弹,提出并实现了以ARM+ FPGA双微处理器为核心的硬件设计方案,采用了模糊PID控制算法,通过优化步进电机控制模式,提高了相位自动微调控制器的控制精度,将步进电机的调整时间由800 ms缩短到100 ms以内;该方案已成功应用于某型弹上系统,实践证明,该设计方案成本低、可扩展性强,能够满足系统控制需求,具有较高的实用性,大大提高了装备维护效率.     

基于LabVIEW的虚拟车身CAN总线节点设计

为研究汽车车载CAN总线节点网络控制功能,通过对大众PASSAT1.8车身CAN总线系统的数据测试得该系统网络控制是以控制数据帧和状态数据帧的传输实现;选用通用CAN总线接口卡,上位机采用LabVIEW编程,设计虚拟左前门控单元节点模型样机;经实验表明,基于PC平台的虚拟车身CAN总线节点可替代实体车身CAN总线节点来实现原车网络控制功能,具有较强的开放性与灵活性,并可为车载CAN总线系统网络设计、测试与教学提供支撑.     

无线机电阻抗结构健康监测系统软件开发

机电阻抗技术是一种新兴的非参数结构健康监测方法,对结构局部微缺陷比较敏感;为了实现基于机电阻抗技术的结构健康监测,采用Visual C++和Matlab混合编程的方式设计和开发了系统监测软件;该软件用于控制现场的无线智能机电阻抗传感器进行数据采集,同时对测量数据进行处理,根据损伤评估算法评定结构健康状况;软件采用Visual C++编写系统人机交互界面和通信接口程序,采用Matlab编写数据处理和损伤评估算法,同时图形化输出运算结果;将两者的优势有机结合,从而缩短了软件的开发周期。     

An integrated head pose and eye gaze tracking approach to non-intrusive visual attention measurement for wide FOV simulators

Eye gaze tracking is very useful for quantitatively measuring visual attention in virtual environments. However, most eye trackers have a limited tracking range, e.g., ±35° in the horizontal direction. This paper proposed a method to combine head pose tracking and eye gaze tracking together to achieve a large range of tracking in virtual driving simulation environments. Multiple parallel multilayer perceptrons were used to reconstruct the relationship between head images and head poses. Head images were represented with the coefficients extracted from Principal Component Analysis. Eye gaze tracking provides precise results on the front view, while head pose tracking is more suitable for tracking areas of interest than for tracking points of interest on the side view.     

Learning-enhanced differential evolution for numerical optimization

Differential evolution (DE) is a simple and powerful population-based search algorithm, successfully used in various scientific and engineering fields. However, DE is not free from the problems of stagnation and premature convergence. Hence, designing more effective search strategies to enhance the performance of DE is one of the most salient and active topics. This paper proposes a new method, called learning-enhanced DE (LeDE) that promotes individuals to exchange information systematically. Distinct from the existing DE variants, LeDE adopts a novel learning strategy, namely clustering-based learning strategy (CLS). In CLS, there are two levels of learning strategies, intra-cluster learning strategy and inter-cluster learning strategy. They are adopted for exchanging information within the same cluster and between different clusters, respectively. Experimental studies over 23 benchmark functions show that LeDE significantly outperforms the conventional DE. Compared with other clustering-based DE algorithms, LeDE can obtain better solutions. In addition, LeDE is also shown to be significantly better than or at least comparable to several state-of-art DE variants as well as some other evolutionary algorithms.     

Fuzzy local maximal marginal embedding for feature extraction

In graph-based linear dimensionality reduction algorithms, it is crucial to construct a neighbor graph that can correctly reflect the relationship between samples. This paper presents an improved algorithm called fuzzy local maximal marginal embedding (FLMME) for linear dimensionality reduction. Significantly differing from the existing graph-based algorithms is that two novel fuzzy gradual graphs are constructed in FLMME, which help to pull the near neighbor samples in same class nearer and nearer and repel the far neighbor samples of margin between different classes farther and farther when they are projected to feature subspace. Through the fuzzy gradual graphs, FLMME algorithm has lower sensitivities to the sample variations caused by varying illumination, expression, viewing conditions and shapes. The proposed FLMME algorithm is evaluated through experiments by using the WINE database, the Yale and ORL face image databases and the USPS handwriting digital databases. The results show that the FLMME outperforms PCA, LDA, LPP and local maximal marginal embedding.     

故障硬盘的数据备份与销毁

硬盘承载着重要数据,它的精密度很高,而且它内部的机械运动快速而准确。一旦这个精密装置的某一部分出现了故障,存储在里面的数据就无法访问,甚至有可能会永久丢失。修复硬盘,找回数据,是数据恢复工程师的神圣使命。一般来说,经修复的硬盘稳定性已大为下降,所以不建议继续使用。但硬盘不用后也不能随意丢弃,因为里面还存储有机密数据,应当将其数据销毁。本文就针对带有坏扇区故障硬盘的数据如何实现数据备份与销毁,以便用户能读出(或销毁)其中重要的数据。     

基于混沌量子进化算法的单交叉口信号控制

城市道路各交叉口交通信号的配时优化和协同控制直接影响整个城市的交通状况.本文以单交叉口模型的交通信号控制问题为背景,构造了以单交叉口滞留的车辆数最少为目标的优化模型.用混沌量子进化算法进行仿真数据求解,得到实时控制的配时方案,并与其它算法的仿真结果进行比较,结果表明该算法对单交叉口的信号配时优化是非常有效的.     

17-4PH沉淀硬化不锈钢氮离子注入及其复合改性的研究

采用N+注入，N-C-O共渗结合N+注入的表面复合改性方法，探索强化17－4PH钢表面的有效途径，该方法赋予基体表面一定深度的改性范围与低摩擦系数，因而强化效果达到最佳。同时还探索了不同时效温度下，基体心部硬度变化的规律。     

铂铑包覆钼合金搅拌器的研制

介绍了铂铑包覆钼合金搅拌器的结构与技术要求,以及搅拌器的制作与使用效果。研制结果表明,国产搅拌器达到了日本同类产品的水平。