CAN总线在组合导航系统中的应用

基于DSP FPGA结构的石油仪器组合导航系统中CAN总线系统设计,为了使数据能够在整个CAN总线网络协调、有效、快速、稳定的传输,提出了一种使用FPGA作为CAN总线节点结构中的核心处理器的设计方法。CAN控制器采用具有SPI接口的MCP2515,利用FPGA实现MCP2515的初始化、数据的发送和接收,实现了DSP处理器的CAN总线扩展应用。该方法由于把CAN节点控制的大量的工作交给FPGA实现,DSP只需要对FPGA中CAN数据接收FIFO和CAN数据发送FIFO进行读写操作,即可完成CAN总线的数据读写操作,大大减轻了DSP的数据处理压力。试验测试及产品应用表明,本设计有效、稳定可靠、可扩展性好,易于修改和移植,具有较强的工程实用价值。     

集成智能化测试系统技术研究应用

运载火箭集成一体化测试发射控制是实现快速发射的重要条件,是未来运载火箭在技术上发展的主要方向。对于目前运载火箭测发周期较长、地面测试环节复杂、设备体形庞大、单体数量众多、结构上集成低等问题,本文研究了运载火箭集成一体化测发控系统在实现快速测发上的应用,从集成、移动操控与环境适应性方面提出了具体技术途径。高速数字总线和BIT箭地一体化综合测试、智能实时判读等技术应用,为实现快速发射创造条件,指出了今后运载火箭快速测试发射技术发展方向。     

基于PCIe总线的双路1394B接口模块设计与实现

为了满足航电系统中前端传感器捕获的图形图像数据实时传输的需求,设计并实现了基于PCIe总线的双路1394B接口模块。该模块通过PCIe接口与主机交互,采用S400β传输模式,软件设计符合标准OHCI规范,支持AS5643协议,异步流包数据收发采用链式队列管理,主机与1394B控制器之间通过DMA操作,实现大数据块的并行处理,两路1394B相互独立,显著提升数据传输性能。测试验证结果表明,该模块具备带宽高、可靠性高、CPU资源占用率低等特点,已在某项目获得成功应用,实现了图形图像数据的实时传输,满足系统设计要求,表现出了良好的稳定性和适应性,具有实践应用价值。     

声波测井仪总线测试接口设计*

为了快速诊断国产声波测井仪或其短节的工作状态是否正常,设计了可与仪器或短节相匹配的总线测试接口电路。针对国产声波类测井仪器的所用总线,设计了Tool control bus(TCB)、High local bus(HLB)、Tool model bus(TMB)、Controller area network(CAN)等总线测试接口。其中TCB、HLB、TMB总线接口在FPGA芯片EP2C20Q240C8控制下实现,软件采用模块化的结构设计;CAN总线接口由单片机C8051F500控制实现。利用了设计的接口电路板,仿真实现了TMB总线的从节点功能,可测试仪器主控短节的工作状态。     

基于CAN总线的中控主机的系统设计

智能中控主机作为多媒体会议室和多媒体展厅等现代化办公场所运转的控制核心,其重要性不言而喻,目前市面上主要采用的是基于RS485总线的传统组网模式,导致系统的实时性较差、容错率较低、功能欠完善,同时成本高昂。针对这种情况,在不允许改动被控设备的工作方式的条件下,提出一种基于CAN总线网络,以嵌入式系统作为主控设备,以各功能驱动模块作为子设备的中控系统。通过CAN总线控制器的优先级仲裁机制,以及制定的带错误反馈的数据包通信协议,实现了对各种被控设备的实时精准控制。该中控主机系统硬件电路简单、功能模块方便扩展、成本低廉并且高效稳定;通过实验测试,所设计的智能中控主机性能良好,达到了规定的行业标准,具有广泛的应用前景。     

LON智能变送器设计与实现

智能化仪器仪表设计研究成为新一代工业制造技术突破的重要瓶颈之一。LON智能变送器是基于LonWorks总线,具有多种信息智能处理的智能变送器,能够将标准的模拟信号、传感器输出的非标准的弱模拟信号及其脉冲信号转换为数字信号,与其它控制仪表实现双向数字通讯。LON智能变送器除了具有数字调零、数字滤波等功能外,其重要特征是具有传感器故障诊断与处理功能,在传感器失效后,能够在一定时间内继续输出有效数据,保证控制系统的稳定和安全。     

DDDU(W)结构优化微机程序系统对客车车身结构的优化设计

利用大连理工大学工程力学研究所研制的结构优化设计程序DDDU(w)对AK6980HK车身骨架结构进行了优化设计。     

Modified circle map model for complex motion induced by a change of shuttle buses

We investigate the dynamic behavior of shuttle buses when passengers switch to another bus B on route B from bus A on route A. By switching from bus A to bus B, the outflow of passengers from route A (inflow of passengers into route B) changes to the periodic inflow of a square wave. The dynamics of the shuttle buses with the change is described by the modified circle map model. The bus schedule and control are closely related to the dynamics. The motion of shuttle buses depends on the inflow rate, its period, and moving time ratio. The shuttle bus displays such complex behavior as periodic, quasi-periodic, and chaotic motions.     

A metaheuristic for the school bus routing problem with bus stop selection

Existing literature on routing of school buses has focused mainly on building intricate models that attempt to capture as many real-life constraints and objectives as possible. In contrast, the focus of this paper is on understanding the joint problem of bus route generation and bus stop selection – two important sub-problems – in its most basic form. To this end, this paper defines the school bus routing problem (SBRP) as a variant of the vehicle routing problem in which three simultaneous decisions have to be made: (1) determine the set of stops to visit, (2) determine for each student which stop (s)he should walk to, and (3) determine routes that lie along the chosen stops, so that the total traveled distance is minimized. An MIP model of this basic problem is developed.     

A post-improvement procedure for the mixed load school bus routing problem

This paper aims to develop a mixed load algorithm for the school bus routing problem (SBRP) and measure its effects on the number of required vehicles. SBRP seeks to find optimal routes for a fleet of vehicles, where each vehicle transports students from their homes and to their schools while satisfying various constraints. When mixed load is allowed, students of different schools can get on the same bus at the same time. Although many of real world SBRP allow mixed load, only a few studies have considered these cases. In this paper, we present a new mixed load improvement algorithm and compare it with the only existing algorithm from the literature. Benchmark problems are proposed to compare the performances of algorithms and to stimulate other researchers’ further study. The proposed algorithm outperforms the existing algorithm on the benchmark problem instances. It has also been successfully applied to some of real-world SBRP and could reduce the required number of vehicles compared with the current practice.