基于 RFID 的物流装备信息监控网络平台设计

集装箱是全球物流运输的核心装备,全球国际货运90%以上都是通过集装箱完成,目前集装箱运输的智能化和信息化技术落后,从而导致物流效率低、海关通关效率低且做不到实时可视化监控.文中基于射频识别和嵌入式微控制器技术开发了用于托盘和集装箱等物流装备的智能数据采集终端,进而设计了基于智能集装箱的现代物流装备物联网系统平台.该平台的广泛应用使现代物流系统的整个供应链信息流畅通,实现了可视化监控,大幅度提高了现代物流效率.为行业应用提供智能集装箱成熟产品和技术方案.     

基于智能定位技术的无人物流车辆智能监控系统设计

传统的无人物流车辆智能监控系统监控图像清晰度差,监控速率慢。为了解决上述问题,基于智能定位技术设计了一种新的无人物流车辆智能监控系统,系统硬件传感器模块选用选用MCJS系列角度传感器,无人物流车辆定位模块选用ZM516X定位模块,支持Mesh网络,监控平台为LAND-LDRTU款无线远程监测终端RTU,内部配置实时监控系统,在C/S模式下设计应用系统程序。实验结果表明,基于智能定位技术的无人物流车辆智能监控系统监控图像清晰度高于传统监控系统42.58%,监控速率高于传统监控系统17.22%。     

变电站继电保护智能监测系统的研究

为解决变电站传统的继电保护装置存在智能化程度低、监测效果差、运维效率低等问题,本文通过分析人工神经网络在线识别机理,提出了一种基于神经网络的变电站继电保护在线监测系统,实现了对变电站多参数的实时动态采集和故障智能诊断,利用组套GUI开发了监控系统界面。经现场调试表明,设计的变电站智能继电保护在线监测系统可以实现对变电站设备的实时在线监控和智能故障诊断,准确采集变电站关键部位的数据并进行分析,实现了对变电站的可视化监控和管理,大大提高了变电站运维效率和质量。     

基于低轨卫星和窄带物联网的智能冷链运输终端系统

针对目前全球范围冷链运输智能系统功耗高、全球覆盖能力差、效率低等问题,以智能冷藏集装箱为研究对象,介绍了一种基于低轨卫星和窄带物联网（NB-IoT）通信技术的智能冷链运输终端系统,并给出了该智能终端系统的系统方案、硬件设计、软件设计、低功耗设计及测试结果.运输终端系统以STM32作为主控制器,集成了温湿度和位置信息等传感器,兼容低轨卫星和NB-IoT两种通信方式,可以实现全球范围内装有该智能终端的冷藏集装箱位置、状态和安全等信息监测控制.通过实际运行表明,该方案可靠,数据传输稳定,具有一定的推广和应用价值.     

未来智能装备制造业发展趋势述评

在具体介绍传统装备制造业存在产量低、质量差、生产时间长、生产效率低、节能降耗差、竞争能力弱等缺陷的基础上,详尽分析了智能制造装备具有的精密化、自动化、信息化、柔性化、图形化、智能化、可视化、多媒体化、集成化、网络化等优点.分别对智能装备制造的绿色化和智能化发展重点、智能制造技术走向以及加快绿色化、智能化步伐的原因进行了探讨.最后指出,智能化、绿色化已成为全球制造业发展的必然趋势,智能制造装备的发展也必将成为世界各国竞争的焦点.     

成品烟分拣系统CAN智能节点设计

针对目前成品烟仓库物流分拣系统总线故障率高、分拣效率低等问题,提出CAN总线与RFID技术相结合的设计构建成品烟仓库物流分拣系统,利用CAN总线的高速数据传输、实时性、高可靠性等特点开发了CAN智能节点.利用LCD触摸屏和MCGS组态软件,提高了分拣系统人机交互的友好性,实现了系统的监控过程的可视化.     

智能矿山低代码工业物联网平台设计

随着智能矿山建设的稳步推进和煤炭企业数字化转型的加速实施,煤矿企业用户业务数字化应用需求呈指数式增长,对业务应用开发效率提出更高要求,传统的煤炭行业应用系统开发模式过度依赖专业厂家,实施周期长、实施成本高、资源重复利用率低,难以满足煤矿用户对快速开发业务应用的管理要求。针对上述问题,提出了一种采用“模型驱动”开发模式的智能矿山低代码工业物联网平台设计方案。基于微服务技术设计了包含数据采集层、数据处理层、数据存储层、数据发布层、人机交互与应用层的平台架构,在每个层级运行平台通过解析引擎解析开发平台配置对应的功能;通过设计数据编码与主数据规范、平台内部数据交互规范、平台接口与服务等构建统一技术体系,实现了煤矿作业现场各类物联网监控对象的统一监管;通过开发低代码组件工具箱,将原本在煤矿各类监控系统软件中需要通过定制化开发的系列通用功能和业务逻辑进行统一封装,形成可直接复用的组件,使其可适应煤矿不同类型监控系统应用,为用户提供一个通过拖拽组件和配置参数等方式即可完成智能矿山应用软件开发的可视化开发环境。应用结果表明,该平台可为煤矿监控类系统提供快速开发平台,满足煤矿用户日常提出的紧急定制化任务...     

基于蓝牙4.0的智能物流监控系统设计

现有的物流监控系统种类繁多,大多数是基于红外、RFID、无线组网等技术.现有物流监控设备大多为离线且配有专用读取设备,不能更高效地实现物流途中信息共享,并且使用不够便捷.因此针对现有物流监控系统存在的不足,设计并实现了一套智能的物流监控系统.结合智能手机的普及性,提出了蓝牙4.0为通信特色的智能物流监控系统的解决方案,结合蓝牙4.0与组网技术,并根据设计方案给出了硬件电路、嵌入式软件程序和Android应用程序,实现用户仅通过手机即可对电子封锁的上封/解封等操作和物流运输的智能监控.实验结果表明,该智能物流监控,能够达到准确的车辆监控效果.将系统应用于物流安全监控上,具有很好的发展应用前景.     

基于WebGIS的第四方物流跟踪及应急系统设计与实现*

随着现代物流的迅速发展,物流模式由第三方物流向第四方物流过渡。作为物流过程的中介者,第四方物流需要对物流过程进行全程跟踪并且作出相应的决策,因此,为第四方物流提供了一个基于WebGIS的物流跟踪及应急决策系统。根据第四方物流业务的需要,对物流过程中涉及的订单即时跟踪、车辆动态监控、应急预案决策生成等进行了有效的模拟和实现。系统将电子地图应用于跟踪与应急决策系统,为用户提供了一个可视化载体,并在运输车辆动态监控过程中融合使用GPS、GPRS和WebGIS技术,实现了物流运送过程中的动态可视化效果;同时在应急     

浅谈铁路集装箱中心站 视频监控系统方案设计

铁路货运是目前重要的物流渠道之一，对于大型物流企业来说，由于—般集装箱中心均有较大面积的工作范围，作业面广泛，依靠人员观看进行监视和管理调度是十分困难的，因此，通过电视监控系统与物流管理软件相结合，搭建统一平台，实现可视化监控管理系统作为现代化物流建设的一个重要组成部分及特征，在安全保卫工作和物流管理方面的作用越来越重大。[编者按]     

Cyber Secure Framework for Smart Containers Based on Novel Hybrid DTLS Protocol

The Internet of Things (IoTs) is apace growing, billions of IoT devices are connected to the Internet which communicate and exchange data among each other. Applications of IoT can be found in many fields of engineering and sciences such as healthcare, traffic, agriculture, oil and gas industries, and logistics. In logistics, the products which are to be transported may be sensitive and perishable, and require controlled environment. Most of the commercially available logistic containers are not integrated with IoT devices to provide controlled environment parameters inside the container and to transmit data to a remote server. This necessitates the need for designing and fabricating IoT based smart containers. Due to constrained nature of IoT devices, these are prone to different cyber security attacks such as Denial of Service (DoS), Man in Middle (MITM) and Replay. Therefore, designing efficient cyber security framework are required for smart container. The Datagram Transport Layer Security (DTLS) Protocol has emerged as the de facto standard for securing communication in IoT devices. However, it is unable to minimize cyber security attacks such as Denial of Service and Distributed Denial of Service (DDoS) during the handshake process. The main contribution of this paper is to design a cyber secure framework by implementing novel hybrid DTLS protocol in smart container which can efficiently minimize the effects of cyber attacks during handshake process. The performance of our proposed framework is evaluated in terms of energy efficiency, handshake time, throughput and packet delivery ratio. Moreover, the proposed framework is tested in IoT based smart containers. The proposed framework decreases handshake time more than 9% and saves 11% of energy efficiency for transmission in compare of the standard DTLS, while increases packet delivery ratio and throughput by 83% and 87% respectively.     

基于区块链原理的集装箱共享模式下集装箱运输流程建模与仿真

针对集装箱存量共享与增量共享均不能有效实施的问题，提出基于区块链原理的集装箱共享模式。首先，阐述基于区块链原理的集装箱共享模式的运作机制；其次，分析在该模式的作用下，集装箱运输流程发生的变化；然后以Petri网理论为基础，使用CPN Tools分别建立传统模式与基于区块链集装箱共享模式下的集装箱运输流程的赋时着色Petri网（CPTN）模型；最后，对模型进行仿真实验，选取不同模式下接收订单到提取空箱装货的时间、路运段空车行驶时间比例、订单损失率、作漏装的集装箱比例这四项指标对比分析。实验结果显示，与传统模式下相比，基于区块链的集装箱共享模式下，发货人提箱时间缩短，集卡空车行驶比例减小5.28%，不再出现因船期与订单时间窗不匹配而损失的订单，作漏装的集装箱比例减小6.99%。通过仿真实验结果可知，基于区块链原理的集装箱共享模式不仅能够弥补集装箱存量共享与增量共享中存在的不足，而且对集装箱运输流程起到优化作用，是集装箱运输行业实现降本增效的一种有效途径。     

Multi-objective hybrid genetic algorithm for quay crane dynamic assignment in berth allocation planning

The development of containers?? transportation has maintained a high momentum since 1961, especially, the containers?? traffic growth reached 10?C11% in recent years. Container terminals play an important role in the transportation chain, in order to response rapidly for the requirement of modern logistics, better resource allocation, lower cost, and higher operation efficiency are needed. In this paper, we introduce the quay crane dynamic assignment (QCDA) in berth allocation planning problem (BAP) and formulate a multi-objective mathematical model considering each berth for container ship with QCDA and number of Quay Crane??s Move. In order to solve this QCDA in BAP problem, we propose a multi-objective hybrid Genetic Algorithm approach with a priority-based encoding method. To demonstrate the effectiveness of proposed mohGA approach, numerical experiment is carried out and the best solution to the problem is obtained.     

基于OpenGL技术的集装箱仿真系统的研究与开发

对靠近海岸线的物流园区集装箱堆场进行研究,发现台风或大风经常造成集装箱吹落或倾覆,这样造成很大的经济损失.研究利用VC和OpenGL开发一个可视化的集装箱仿真系统,该系统通过气象部门所提供的风速,能够预测物流园区中的集装箱是否安全.系统使用OpenGL中的纹理映射和视点变换,并以一种直观的、可视化的方式呈现给现场操作人员.现场操作人员可以根据系统的提示信息,在台风来临之前对将会被台风吹落的集装箱做好加固措施,以达到减小经济损失的目的.     

海铁联运港口混合作业模式下轨道吊与集卡协同调度

在集装箱海铁联运港口中,铁路作业区作为连接铁路运输和水路运输的重要节点,其装卸效率将影响集装箱海铁联运的整体效率。首先,对比分析了“船舶-列车”作业模式和“船舶-堆场-列车”作业模式的特点,并结合海铁联运港口实际作业情况提出了混合作业模式。然后,以轨道吊完工时间最短为目标构建混合整数规划模型,既考虑了班列和船舶的作业时间窗约束,又考虑了轨道吊间干扰和安全距离、轨道吊和集卡接续作业和等待时间等现实约束。针对遗传算法在局部搜索能力方面的不足,将启发式规则与遗传算法相结合设计了求解轨道吊与集卡协同调度问题的混合遗传算法（HGA）,并进行了数值实验。实验结果验证了所提模型和混合算法的有效性。最后通过设计实验分析集装箱数量、岸边箱占比、轨道吊数量和集卡数量对轨道吊完工时间和集卡完工时间的影响,发现同等集装箱数量下岸边箱占比提高时,应通过增加轨道吊数量来有效缩短完工时间。     

集装箱海运空箱分派随机规划模型研究*

通过对海运集装箱空箱分派过程的仔细分析,在考虑需求不确定性的基础上引入了空箱运输能力的不确定性这一重要因素,建立了同时考虑供需平衡约束以及需求和空箱运输能力不确定性的空箱分派随机规划模型,并应用机会约束规划方法对模型求解.最后通过数值仿真,揭示了运输成本、租箱成本和存储成本等参数和空箱运输能力的不确定性对集装箱空箱分派策略的影响机制.     

A hybrid differential evolution algorithm for multiple container loading problem with heterogeneous containers

We consider a multiple container loading problem, commonly known as the three-dimensional bin packing problem (3D-BPP), which deals with maximizing container space utilization while the containers available for packing are heterogeneous, i.e., varying in size. The problem has wide applications in cargo transportation, warehouse management, medical packaging, and so on. We develop a differential evolution (DE) algorithm hybridized with a novel packing heuristic strategy, best-match-first (BMF), which generates a compact packing solution based on a given box packing sequence and a container loading sequence. The effectiveness of the proposed algorithm is evaluated on a set of industrial instances and randomly generated instances. The results show that the proposed algorithm outperforms existing solution approaches in terms of solution quality.     

基于PocketPC的集装箱结点站管理信息系统的分析与实现

Pockt PC是一种功能强大的掌上电脑,广泛应用与仓库管理、运输、物流、货物追踪等行业中.文中主要介绍了基于PocketPC的集装箱结点站管理信息系统的分析与实现.     

Application of a combined fuzzy multiple criteria decision making and optimization programming model to the container transportation demand split

The container transportation demand split is one of the most important decision issues for government transportation departments and port organizations. In previous studies, many researchers assumed that the shipping carrier would aim to minimize the total operation cost by selecting an appropriate port as the most favorable one to call, and the shipper would aim to minimize the inland freight cost by selecting the nearest port as the most favorable one to import and export international trade containers. Thus, a number of mathematical programming models have been developed. But in practice, the shipping carrier not only aims to minimize the total operation cost but also takes into account other criteria such as the volume of containers and port facility conditions when choosing an appropriate port as the most favorable one to call. The shipper not only aims to minimize the inland freight cost but also takes into account the frequency of ship callings when choosing an appropriate port as the most favorable one to import and export international trade containers.Thus, the purpose of this paper is to formulate a combined fuzzy multiple criteria decision making and optimization programming model for solving the container transportation demand split problem. There are two stages in this combined model: in stage one, we first compute the container transportation demand split rate by using fuzzy multiple criteria decision making (MCDM) method; whereas in stage two, an optimization mathematical programming network model is proposed for determining the inland origin destination (O-D) of import/export containers. The utilization of the proposed model is demonstrated with a case of Taiwanese ports. The results show that the proposed combined fuzzy MCDM and optimization programming model can be used to explain the container transportation demand split practice.     

An efficient computational procedure for determining the container-loading pattern

Supply chain and global logistics are driven by strategically focusing on core competences, outsourcing manufacturing to pursue higher value proposition in the supply chain, radically improving the return of capital investments and providing total solutions to targeted customers. The container-loading research has important industrial and commercial application for global logistics. In practice, loading pooled shipment into containers is a complex procedure that has relied largely on the workers’ experience. We developed an efficient computational procedure involving three-dimensional cutting for determining near-optimal container-loading patterns to minimize the waste of container space. We used numerical examples from a motor company that imports key components from Japan, produces parts in Taiwan, and assembles cars in China to estimate its validity and discussed the effectiveness of the proposed solution. This study concludes with a discussion of future research.