基于PB语言的自动称量管理系统

电子汽车衡是目前港口普遍使用的一种称重仪器,讲述了基于PB语言的汽车衡自动称量管理系统。介绍了新系统硬件组成、软件方案和系统功能。该系统增强了汽车衡管理的自动化程度,提高了称重的可靠性和准确性。     

称重传感器的使用和调试

随着微处理机的出现，工业生产过程自动化程度的不断提高，称重传感器已成为过程控制中的一种必需的装置。目前，称重传感器几乎应用到了所有的称重领域。本文以SCS全电子汽车衡为例，介绍称重传感器使用和调试的经验。     

集装箱称重计划任重道远

近日,国际海事组织(IMO)危险货、固体货物和集装箱分管委员会(DSC)第17次会议在伦敦召开。会议集装箱安全工作组,就集装箱称重问题进行了漫长的讨论,对集装箱称重计划基本达成了共识,并对现有的SOLASVI/5进行了修改,制定了SOLASVI/2修正案草案。明确了托运人须承担验证货运集装箱总重量的责任。验证方式首选对集装箱进行整体称重;为什么对集装箱进行称重?如果法规生效,又将对集装箱运输业产生哪些影响?     

香港海事处颁布载货集装箱总重量验证指引

正香港海事处日前颁布香港境内载货集装箱总重量验证指引,提供两种载货集装箱总重量的验证方法。方法一:当集装箱的装箱和封条完成后,托运人可安排使用海事处认可的称重设施进行载货集装箱称重,所获得的验证总重量必须在运输文件中作出声明,并于集装箱抵达码头闸口前提交给码头及承运人。集装箱被认证的称重设施称重后,托运人必须取得显示相关称重     

两大主要船旗国质疑集装箱称重计划

巴拿马和塞浦路斯两大船旗国就集装箱称重提案提出关切．认为还有更多工作要做，必须在立法生效之前全面考虑所有方面，但并未原则反对称重提案。ITF对这两个船旗国进行了抨击，认为此举将导致集装箱称重规则延期执行。     

电子汽车衡的维护与保养

为保障汽车衡的良好性能,天津港太平洋国际集装箱码头加强了对汽车衡的维护与保养。介绍电子汽车衡概况及其组成部分。着重介绍电子汽车衡的维护与保养和故障排除。总结了一些实用经验。可供参考。     

集装箱称重将明显提高安全水平——世界航运公会（WSC）和国际航运协会Ocs）

IMO考虑对集装箱进行称重．虽然没有就是否成立强制性机制达成协议，但是该决定仍得到船东的欢迎与支持。WSC和ICS日前发表联合声明称．集装箱称重将会明显提高集装箱、船员、岸上操作和运输人员以及船上其他货物的安全水平。     

吊具称重的时代来了

正集装箱装船之前就必须提交出口集装箱查核总重量(VGM)的要求马上就要实行了,其中最大的一项挑战是如何取得VGM。在本文中,我们假设吊车操作员工不把集装箱搬离货车放到地秤上进行称重。也就是说,要称的是货车、拖车和集装箱三者的总重量。现有的用于计算集装箱重量的方法有两种:一种方法是对卸载集装箱后的空货车和拖车进行称重,然后从总重量中减去车的重量。另一种方法是从总重量中减去车辆自重得到集装箱重量。     

无线数字动态轮重仪的设计与应用

研制了一种适用于高速公路计重收费或治理超载车辆的动态汽车衡。采用特殊的力学结构设计，保证了称重板动态测量的精度，并将无线传输技术应用于测量数据的近程传输，克服了野外工作烦琐的远距离布线施工，利用GPRS功能实现了远程设备监控、诊断和维护功能。     

TTZ45型集装箱正面吊运机称重算法的研究

集装箱正面吊运机力矩限制器通常采用变幅油缸取力方式，使用两个油力传感器分别测得上下油缸的油压，得到压力差值，然后结合吊运机的其他结构参数，算得吊重重量。影响称重精度的因素除系统硬件采样变换等环节的误差外，还有系统软件中的理论计算公式与实际情况的差异，主要来自臂架重心的不确定性和臂架结构变形的复杂性。为了减小误差，提高称重精度，必须对集装箱正面吊运机的称重算法进行优化。     

双垂直线路桥大型箱梁运输施工技术

为满足施工需要,根据现场实际情况对两种施工方案进行比对分析,选择了小半径大角度转弯运输箱梁的方案。通过对传统轮胎式运梁小车改进,特制出五轴轮胎式运梁小车。采用该运梁小车成功解决了大吨位大跨度大型箱梁在小转弯半径上实现大角度转弯的技术难题。结果表明,特制五轴轮胎式运梁小车是解决狭小施工场地内大角度运梁的有效方法。     

码头集卡运输线路的模型研究及设计

集装箱码头的集卡调度优化问题已经应用到生产领域，但其中有一个重要的问题就是集卡运输线路的选择还相对研究较少。运用了线性规划的RVP模型设计了一个算法，并在模拟程序中进行实现，效果较好。计划在新的集装箱码头管理系统中将该模型融合进去。     

Application of El Farol model for managing marine terminal gate congestion

Truck queuing at marine terminal gates has long been recognized as a source of emissions problem due to the large number of trucks idling. For this reason, there is a great deal of interest among the different stakeholders to lessen the severity of the problem. An approach being experimented by some terminals to reduce truck queuing at the terminal is to provide live views of their gates via webcams. An assumption made by the terminals in this method is that truck dispatchers and drivers will make rational decisions regarding their departure times such that there will be less fluctuations in truck arrivals at the terminal based on the live information. However, it is clear that if dispatchers send trucks to the terminal whenever the truck queues are short and not send trucks when the truck queues are long, it could lead to a perpetual whip lash effect. This study explores the predictive strategies that need to be made by the various dispatchers to achieve the desired effects (i.e. steady arrival of trucks and hence less queuing at the seaport terminal gates). This problem is studied with the use of an agent-based simulation model and the solution to the well known El Farol Bar problem. Results demonstrate that truck depots can manage (without any collaboration with one another) to minimize congestion at seaport terminal gates by using the provided real-time gate congestion information and some simple logics for estimating the expected truck wait time.     

基于元胞自动机的集装箱码头前沿水平运输模型研究

为了开发能更细致的模拟集卡行驶方式及特点的新模型,应用元胞自动机理论,建立以单个集装箱卡车车位为元胞个体的集装箱码头前沿交通流二维仿真模型。通过对该模型的仿真试验,证实该模型能输出更接近于现实的仿真数据结果。     

Impact of container chassis management practices in the United States on terminal operational efficiency: An operations and mitigation policy analysis

Existing policies designed to mitigate the environmental and social impacts of truck queuing at maritime terminals often focus on congestion problems outside of the terminal gate, targeting a reduction in the waiting and turn time of trucks as the measure of success. This paper evaluates the impact that intra-terminal truck and equipment movements have on the terminal’s overall performance and the implications that these movements have on the effectiveness of current mitigation policies. Through a simulation of terminal processes occurring at Southern California ports it is shown that measures driving reductions in truck turn times impose greater operational loads on terminal equipment, essentially transferring savings in truck turn time rather than eliminating it in terms of the overall system. Consequently, the paper finds that total truck and cargo handling equipment movement and operational time constitutes a more accurate measure of the effectiveness of policies seeking to mitigate the impacts of truck operations at marine terminals.     

重型汽车下河斜坡码头合理纵坡研究

从车、船两方面因素对重型汽车下河斜坡码头合理坡度进行研究。以常见重型自卸汽车及一般内河船型为研究对象,重点分析汽车爬坡能力、下坡能力及码头前沿设计水深对坡度的约束。结果表明,码头斜坡道合理的坡度范围约在5.5%～9%,且汽车总质量越大,船舶吃水越深,下河斜坡道坡度可选择的范围就越小,甚至趋于一个定值;同时斜坡坡长不宜超过150 m,且车速宜控制在10 km/h以内。     

集卡调度方式对集装箱港区碳排放的影响

集卡已成为集装箱港区内的主要碳排放源,尤其两艘大型集装箱船舶同时作业时,港区内集卡碳排放问题严重。针对该情况下集卡调度模式的特征,基于智能体仿真技术构建集装箱码头生产作业微观仿真模型,定量分析传统先卸后装、双船一装一卸、同贝同步装卸工艺下集卡调度方式与集卡配置数量对船舶在港时间、集卡碳排放量的影响。实例表明,采用同贝同步装卸作业方案可保证装卸效率,并有效减少集卡碳排放,而集卡配置数量只对集卡怠速行驶产生的碳排产生影响。     

轻型集装箱跨运车的开发及应用

通过整机轻型化、平顺性、防偏载等关键技术研究开发出的轻型集装箱跨运车具有显著的新颖性。该机的作业效率高于拖挂车的水平运输方案，可应用于专业集装箱码头、货场和中转站等场所。     

Modeling yard crane operators as reinforcement learning agents

Due to the importance of drayage operations, operators at marine container terminals are increasingly looking to reduce the time a truck spends at the terminal to complete a transaction. This study introduces an agent-based approach to model yard cranes for the analysis of truck turn time. The objective of the model is to solve the yard crane scheduling problem (i.e. determining the sequence of drayage trucks to serve to minimize their waiting time). It is accomplished by modeling the yard crane operators as agents that employ reinforcement learning; specifically, q-learning. The proposed agent-based, q-learning model is developed using Netlogo. Experimental results show that the q-learning model is very effective in assisting the yard crane operator to select the next best move. Thus, the proposed q-learning model could potentially be integrated into existing yard management systems to automate the truck selection process and thereby improve yard operations.