铁路调度集中系统实时备份与应急切换技术

分散自律调度集中系统(以下简称CTC系统)是铁路运输的核心信息系统,数据的可靠性保障十分重要.传统方法通过人工定期进行数据库备份,并在出现故障时进行人工恢复,无法保障铁路运输系统的不间断正常运行.本论文基于Oracle Data Guard技术设计实现了CTC系统数据库数据实时备份方案,对主用数据库数据动态自动备份,在备份和恢复过程中对用户完全透明,不影响调度员和车站值班员的正常使用,在占用数据库资源最小的情况下执行备份过程;当主用数据库发生问题或日常进行主备库倒换试验,通过数据库维护人员的简单操作,即可进行数据库业务的应急切换.在实际应用过程中,备用数据库和应急切换机制为缩短CTC的调度指挥中断时间起到了关键作用.     

智能家居中基于实时电价的家用电器调度方案

针对现有调度方案中不能解决电器使用的不确定性和可再生能源的问题,提出了一种考虑不确定性的基于实时电价的家用电器任务调度方案,该方案采用线性规划的建模方法,以最小费用支出为优化目标,兼顾了PV光伏系统、家用蓄电池以及向电网出售剩余电力情况下的能量流动,用随机规划方法和蒙特卡罗模拟来解决电器使用过程中的不确定性,保证了用户满意度.最后经实验证明,该方案具有重要的实际意义.     

基于图像受噪程度的改进模糊加权均值滤波

根据高斯噪声密度大、噪声强度的波动范围宽,其污染图像不仅每一个像素灰度级都会受影响,而且即使是同一灰度级受污染的程度也会不同的特点和传统的图像模糊滤波算法在图像细节保护方面上的不足,提出基于图像受噪程度的改进模糊加权均值滤波算法,该算法根据图像各像素点的受噪程度,得到首次滤波图像和原图像估计直方图,根据该直方图确定模糊隶属度函数,然后对首次滤波图像中灰度小于25的像素点进行模糊加权均值滤波,该算法在不需要期望图像和高斯噪声方差的情况下能有效地去除噪声,同时能够很好地保护图像细节信息。     

Robust periodically time‐varying horizon finite memory fault detection filter design for polytopic uncertain discrete‐time systems

In this paper, a robust periodically time‐varying horizon finite memory fault detection filter (PTVHFM‐FDF) is proposed to generate residual signal for the purpose of system monitoring. The major advantage of PTVHFM‐FDF is that finite historical data can be sufficiently utilized to enhance the robustness of fault detection against model uncertainty and external disturbance. The analysis, design, and application of PTVHFM‐FDF consist of several steps. Firstly, a periodic time‐varying residual error system is constructed on the basis of augmented method and time domain partition method. Secondly, in facilitating robust stability and performance analysis, the time‐varying residual error system is further transformed into a polyhedral time‐invariant system on the basis of time lifting technique. Thirdly, less conservative PTVHFM‐FDF analysis and design conditions are then obtained on the basis of Finsler relaxation lemma and slack variable structure definition. Fourthly, choices of memory window horizon parameters are properly suggested on the basis of a compromise between FDF robustness and its structural complexity. Finally, an integrated design and application algorithm of PTVHFM‐FDF is summarized. Effectiveness of PTVHFM‐FDF is verified through three examples. Copyright © 2017 John Wiley & Sons, Ltd.     

Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

In this paper, we design time–frequency localized three-band biorthogonal linear phase wavelet filter bank for epileptic seizure electroencephalograph (EEG) signal classification. Time–frequency localized analysis and synthesis low-pass filters (LPF) are designed using convex semidefinite programming (SDP) by transforming a nonconvex problem into a convex SDP using semidefinite relaxation technique. Three-band parameterized lattice biorthogonal linear phase perfect reconstruction filter bank (BOLPPRFB) is chosen and nonlinear least squares algorithm is used to determine its parameters values that generate the designed analysis and synthesis LPF such that the band-pass and high-pass filters are also well localized in time and frequency domain. The designed analysis and synthesis three-band wavelet filter banks are compared with the standard two-band filter banks like Daubechies maximally regular filter banks, Cohen–Daubechies–Feauveau (CDF) biorthogonal filter banks and orthogonal time–frequency localized filter banks. Kruskal–Wallis statistical test is employed to measure the statistical significance of the subband features obtained from the various two and three-band filter banks for epileptic seizure EEG signal classification. The results show that the designed three-band analysis and synthesis filter banks both outperform two-band filter banks in the classification of seizure and seizure-free EEG signals. The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.     

Development of a 3D HUD using a tunable bandpass filter for wavelength multiplexing

A 3D stereoscopic head‐up display using a tunable bandpass filter to perform left and right image spectral separation is presented. Using a single filter reduces the size and the cost of the head‐up display optical engine and enables each spectral band to be accurately tuned. Experiments performed on the first prototype demonstrate the ability to continuously tune the bandpass frequency on 30‐nm range while keeping a 20‐nm bandwidth. Such a system avoids the use of a bulky and costly rotating wheel and enables the use of holographic optical elements known to be wavelength selective.     

石油化工仪表防雷接地系统设计与实现

为了提高石油化工仪表的防雷安全性,进行防雷接地系统的优化设计,提出一种基于漏感和励磁电感增益分配和检波控制的防雷接地系统设计方法,基于麦克斯韦全电流定理,进行石油化工仪表防雷接地的电磁场分析,以双运放LM358放大器为核心进行石油化工仪表防雷接地系统电路设计,主要包括了交流放大器设计、滤波器设计、检波器设计和直流放大器设计,在检波设计中采用8阶高通滤波器(S3529)并联,提高防雷接地系统的输出运放性能,最后进行系统调试和电路测试,结果表明,采用该系统进行石油化工仪表防雷接地设计,防雷的阻带衰减大于51dB,对雷击信号具有较好的高通滤波和低通滤波性能,较好地保护了石油化工仪表安全。     

测控数据实时监测软件设计方法研究

测控数据实时监测软件是测控系统中的关键分系统之一,承担着大量测控信息的实时监视任务,由于其监测的数据具有信息量大、发送频率高、种类多样等特点,如何提升软件的性能和效率,成为了测控软件领域的一项重要课题;为实现该软件信息监测功能实时、全面、可靠,从软硬件平台、软件架构和算法设计等方面开展研究;采用多线程设计实现大量并行数据的接收,利用面向对象程序设计方法使数据处理层和展现层分离,对有曲线显示需求的数据存储方法进行了算法优化,从而实现软件的全面效能提升设计;设计的软件经实际环境测试,设计方法能够有效提升软件的效能,保证了测控数据监测功能的实时性和可靠性,增强了测控数据实时监测软件的数据承载能力;同时该方法设计的软件具有较好的可扩展性和可维护性。     

面向安全关键嵌入式系统的时钟同步设计

为了满足安全关键性实时嵌入式系统对实时行为正确性和确定性的要求,本文应用ETSEC网络控制器的硬件时间戳特性, ReWorks嵌入式实时操作系统的实时特性,结合IEEE 1588精密度时钟同步协议,设计并实现了一个面向安全关键性领域的时钟同步系统原型.其同步精度达到100纳秒以内,并通过软件插桩测试和验证了该时钟同步系统的正确性和精度.     

基于无指导学习的微博评论分析方法

该文以一种有效的方法寻找出有价值的微博评论,这对于读者更高效地阅读评论,为舆情分析、文本挖掘等任务提供支持,均具有重要的应用价值。针对微博及其评论文本短小、内容发散等特点,该文提出一种基于无指导学习的微博评论分析方法,该方法通过互联网搜索引擎扩展微博文本,基于相关性计算自动构造正负训练用例,生成特定的某条微博评论分类模型,通过该模型对评论的价值性进行评估。实验结果表明,该方法能够比较好地识别出评论的价值。