高校体育多媒体教学平台系统的建设研究

本文从当前高校体育教学的周期短、学时少、教学方法单一的特点出发,充分的利用现代计算机网路多媒体技术,设计一套符合高校体育教育的多媒体教学平台系统,以满足学生课余时间的自主学习,增加教学的延伸性、娱乐性,为高校体育教育目标的实现提供保障。     

Design and Application of Discrete Sliding Mode Control with RBF Network-based Switching Law

This article proposes a novel approach combining exponential-reaching-law-based equivalent control law with radial basis function (RBF) network-based switching law to strengthen the sliding mode control (SMC) tracking capacity for systems with uncertainties and disturbances. First, SMC discrete equivalent control law is designed on the basis of the nominal model of the system and the adaptive exponential reaching law, and subsequently, stability of the algorithm is analyzed. Second, RBF network is used to form the switching law in a direct and online manner with sliding-mode-related inputs and by approximating evaluation function; and the method to adjust its parameters is devised. Finally, comparable experiments are carried out to verify the application of the proposed approach to an inner-axis driven by a direct current (DC) torque motor through extra-low speed servo for a high precision flight simulator, and the axis works under deteriorating conditions such as periodically fluctuating torques of motor, nonlinear friction, and time-varying model parameters. The results show that the combined SMC can effectively improve the servo performance, for instance, to a stable 0.000 08 (°)/s speed response, the tracking error would be within 0.000 08° in 98% of operating times. Moreover, the hybrid nature of the approach imparts the RBF network the features of removing offline training and ease to set initial parameters.     

计算机多媒体辅助教学软件设计思想

本文根据几年来制作多媒体课件的实践，详细，系统地阐述了多媒体辅助教学软件开发的总体设计思想。     

全球卫星导航星座网络协议体系与运行模式

针对全球卫星导航星座网络建设初期或论证阶段所涉及的网络体系结构、协议体系及相关组网等技术问题,开展了基于导航星座星间链路构建空间信息网络的技术研究,分别提出了由子网、接入网、骨干网等节点及其相互之间星间、星地无线链路构成的分层网络系统结构,设计了兼容遥控、遥测、测量与网络交互支持等业务的基于IP over CCSDS(基于空间数据系统咨询委员会标准的空间链路承载互联网协议业务)的协议体系,给出了全系统基本通信业务运行模式等。与传统高轨卫星通信系统相比,该星座网络具有高覆盖、低时延、随遇接入等优点,可实现星座导航性能与中低轨及地面用户通信性能的全方位提升,相关结果对我国全球卫星导航星座网络技术研究具有一定的参考意义。     

多媒体煤矿安全监测管理系统研究

介绍了现有的煤矿安全监测和安全考勤管理系统的特点及缺陷，探讨了如何将多媒体计算机技术应用于煤矿安全监测管理系统。该系统具有实时监视、紧急救援和事故分析三大特点。     

HSDB网络稳定性的研究

高速数据总线（ＨｉｇｈＳｐｅｅｄＤａｔａＢｕｓ，ＨＳＤＢ）是新一代航空电子系统的数据总路线，ＨＳＤＢ网络实际上是基于线性令牌总线的一个专用计算机局域网，在网络上负载较重且时间非苛刻的消息到达是一般过程的条件十分别讨论了网络的局域和全域稳定性，并导出了保证整个网络稳定的令牌握有定时器最小值，同时给出了如何根据应用去调整得到的理论值。     

一般高速数据总线网络的吞吐量分析

分析了一般高速数据总线网络优先权方案的特性，建立了一般ＨＳＤＢ网络多优先权的平均吞吐量模型，导出了不同优先权的平均吞吐量解析表达式，并通过软件仿真验证了由得到的解析表达式。     

面向任务的空间信息网络体系结构可重组设计

针对空间信息网络体系结构设计和其使命任务的多重性、多维性的问题,提出了一种体系结构可重组设计方法。首先,介绍了空间信息网络及其体系结构的国内外发展现状,分析了研究空间信息网络体系结构可重组设计的需求。其次,结合空间信息网络的概念、结构和特征,建立了松耦合、兼容性、隔离性和可解构的可重组设计原则。同时,定义了管理中心（RMC）和资源中心（RRC）的内涵,分析了RMC和RRC的运行机制,从目标、拓扑、实体、数据、方案5个维度出发提出了一种形式化的可重组网络体系结构模型,并给出了可重组网络体系结构的实现算法流程。最后,以某反导作战活动为例进行了体系结构可组构设计的案例分析,基于STK平台进行可重组网络的仿真演示,着重展示和验证了可重组设计思想在实践中的具体应用,达到了预期目的。     

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10?Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.