Parallel Distributed Implementation of Truss Optimization on a Local Area Network

A two-level optimization method for the design of complex truss and parallel distributed implementation on a LAN is presented using parallel virtual machine (PVM) for Win 32 as message passing between PCs. The volumes of truss are minimized by decomposing the original optimization problem into a number of bar optimization problems executed concurrently and a coordinate optimization problem, subject to constraints on nodal displacements, and stresses, buckling and crippling of bars, etc. The system sensitivity analysis that derives the partial derivatives of displacements and stresses with respect to areas are also performed in parallel so as to shorten the analysis time. The convergence and the speedup performances as well as parallel computing efficiency of the method are investigated by the optimization examples of a 52-bar planar truss and a 3 126-bar three-diraensional truss. The results show that the ideal speedup is obtained in the cases of 2 PCs for the 3 126-bar space truss optimization, while no speedup is observed for the 52-bar truss. It is concluded that (1) the parallel distributed algorithm proposed is efficient on the PC-based LAN for the coarsegrained large optimization problem; (2) to get a high speedup, the problem granularity should match with the network granularity;and (3) the larger the problem size is, the higher the parallel efficiency is.     

基于多Agent的雷达设备远程故障诊断系统

针对雷达设备的故障检测需求,设计由多个Agent组成的远程故障诊断系统软件结构;提出结合结构和故障的综合方法对雷达诊断问题进行分布式任务分解,明确故障问题;阐述多Agent之间合作完成诊断任务的过程;对系统的硬件结构进行层次划分和功能设计。通过实例说明系统诊断功能的实现。     

路面附着系数的自适应衰减卡尔曼滤波估计

为了获得实时、准确的路面附着系数,进一步提高观测路面附着系数算法的精度和收敛速度,结合非线性车辆动力学模型和轮胎力修正模型,搭建分布式驱动电动汽车联合仿真平台,提出一种基于自适应衰减无迹卡尔曼滤波的路面附着系数观测算法。该算法设计与各轮对应的路面附着系数观测器,应用协方差匹配判据对观测器发散趋势进行判别,设计自适应加权系数修正预测协方差,以增强新近观测数据的利用率;同时采用次优Sage-Husa噪声估计器对未知的系统过程噪声进行估计,抑制观测器的记忆存储长度,调整过程噪声和测量噪声的均值与协方差,提高观测器的跟踪能力。利用分布式驱动电动汽车分别进行高、低附着路面和对开路面直线制动试验,并将自适应衰减无迹卡尔曼滤波路面附着系数观测器的观测结果与无迹卡尔曼滤波观测值、参考路面附着系数进行比较和分析。结果表明：高附着路面条件下,所设计的算法估计误差可控制在0.64%以内;低附着路面条件下,所设计的算法估计误差可控制在1.03%以内;对开路面条件下估计误差可控制在1.26%以内;自适应衰减无迹卡尔曼滤波算法相比无迹卡尔曼滤波算法响应速率更快,具有更高的估计精度和较强的自适应能力,估计结果整体上维持稳定,能够适应各种不同路面的估计。     

Antisymmetric thermal buckling triggered by dual distributed buoyancy sections

Rogue buckles may occur for unburied subsea pipelines operating under high temperature and high pressure conditions. Distributed buoyancy section (DBS) is often installed to trigger pipeline lateral buckling. Single distributed buoyancy section (SDBS) is normally adopted to trigger a symmetric lateral buckling mode. But in some cases, dual distributed buoyancy sections (DDBS) with a gap between them are utilised to trigger an antisymmetric lateral buckling mode. This paper concerns the behaviour of antisymmetric lateral buckling triggered by DDBS. First, the locations of the maxima of the deflection and bending stress are determined. Then, comparisons of the post-buckling behaviour between antisymmetric buckling mode, triggered by DDBS, and symmetric buckling mode, triggered by SDBS, are presented and discussed. The influences of the spacing between dual buoyancy sections and the parameters of the DBS on the buckled configuration and post-buckling behaviour are presented. Finally, the effects of the DBS on the minimum critical temperature difference, the maxima of the deflection and stress are discussed. The results show that the maxima of the deflection and stress of the antisymmetric mode are much smaller than that of the symmetric mode under the same operating conditions. During the design process, the spacing between dual buoyancy sections, the length and the weight ratio coefficient of the DBS should be determined in sequence.     

全电子联锁开发和应用研究

从计算机联锁系统的发展出发,给出全电子联锁系统的定义,分析全电子联锁系统的特点,与现有联锁系统的主要区别。在开发和应用方面,研究应遵守的标准和规范,提出安全要求,并对信号机和道岔模块完成的功能进行重点讨论。     

桥梁健康监测系统中的大数据分析与研究

由于分布在桥梁上的传感器长时间连续地采集数据,传输的数据量非常大,传统的桥梁健康监测系统不能够完全应对海量监测数据,为此,提出了一种基于K线图时间片驱动的滑动窗口数据流处理模型,对传感器网络中的数据流进行快速有效地采集,并且能够减少桥梁监测的数据存储量。基于单一服务器节点的索力统计评估系统,在分析海量数据时存在计算瓶颈,利用集群的分布式并行计算,提出了基于Map/Reduce的索力并行处理模型,实验结果表明,在该模型下处理索力监测历史大数据,可以明显减少专家系统的分析评估时间。     

水下传感器网络中的分布式参数估计算法

水下无线传感器网络的主要应用都可以归结为参数估计问题。由于其能量和带宽的限制,设计能量高效的参数估计算法,是水下无线传感器网络中信号处理研究领域的核心任务。针对多跳水下无线传感器网络,提出了一种基于压缩数据的分布式参数估计算法。仿真试验表明,该算法具有较高的能量利用率和一定的鲁棒性,而且均方误差性能相比已有的分布式参数估计算法也得到了大幅的提高。     

基于模糊加权的分布式IMMJPDA算法

提出了一种基于模糊加权的分布式交互多模型联合概率数据互联算法.该算法在融合中心采用模糊加权方法对不同传感器关于同一目标的模型概率、状态估计及其协方差进行融合,而模糊权值为各传感器关于各目标的状态估计协方差的迹的隶属度.最后通过计算机仿真验证了该算法的正确性和有效性.     

数字分布式系统时间同步CAN总线协议研究

分布式控制系统的时间同步问题是一个令人关注的问题,本文提出了一种含时间向量的数据信息传输与处理的CAN总线顶层标准框架,可为全船现场单元提供一种时间向量的数据帧定义、同步和异步信息权限分配等实时标准顶层框架,本协议可用于舰船电力系统,为电能分布式实时控制奠定基础。     

一种改进的无线传感器网络安全数据融合算法

首先对无线传感器网络数据融合的相关技术进行比较,在分布式数据融合算法的基础上提出了一种改进高效数据融合算法,利用NS2仿真平台对其传输开销进行仿真测试。仿真结果表明,相比分布式数据融合算法,所提的算法能够更有效地减少传输开销并且节省节点能耗。