自动化散货码头装卸作业存在的问题与对策

针对目前国内已投入运营的自动化散货码头在装卸机械设备配置、功能区域划分、安全管理等方面存在的问题进行分析。提出针对性的解决对策,以进一步提高自动化散货码头的装卸作业效率并确保作业安全。对自动化散货码头的技术发展进行展望,供自动化散货码头建设或升级改造时参考和借鉴。     

散杂码头设计中节能增效措施的应用

针对码头工程中如何多方位将节能增效措施融入到设计中的问题,以长江江苏段某散杂码头及其堆场的设计为例,在工艺、结构、电气等方面采用多方位比较的方法,工艺采用装船机、取料机和皮带机变频联动系统、旋转式过渡皮带车以及三工位头部伸缩装置等措施,结构方面陆域轨道基础采用新型专利,电气方面采用风光互补路灯及岸电系统等不同的节能增效措施,使项目更经济合理、效益显著。     

汉江雅口航运枢纽泄水闸工程地基处理

汉江雅口航运枢纽工程泄水闸地基为不均匀的砂砾石土层,建基面局部为粉细砂薄层,砂砾石土层局部含有粉细砂透镜体或大块卵石。针对地基沉降量大和砂砾石土层分布不均匀的问题,提出了长螺旋钻孔压灌桩复合地基处理方案,并在现场代表性区域进行了成桩试验检测。结果表明:该地基处理方案技术可行、质量稳定、生态环保,适宜于本工程的应用,具有推广价值。     

船用离心泵状态监测

实现机舱设备实时状态监测及评估是智能船舶以及无人机舱发展过程中的重要部分,也是事后维修、定期维修向视情维修转变过程的关键技术.本文利用最小二乘多项式拟合法对实验数据进行拟合,得到离心泵Q-H特性曲线拟合多项式.在某一进出口压差下,比较拟合流量和监测流量之间的差值来表征离心泵实时性能状态,并通过设置不同程度的泄露故障验证该方法的有效性.相比于用CFD软件建模仿真以及监测振动等方法,该方法可行性强、简单实用、成本较低,具有重要的实际工程应用价值.     

船舶运动姿态测量系统设计与实现

为了获取海上航行船舶及自航模试验中船模的姿态参数,设计一种基于MEMS(微机电系统)技术的波高倾斜一体化传感器的船舶运动姿态测量系统.此系统通过MEMS波高传感器对船舶升沉信息进行采集,利用倾角传感器对船舶的纵摇和横摇姿态信息进行采集,采集到的信息经多路A/D转换后送入单片机进行处理,实时得出船舶运动的升沉、纵摇及横摇变化.经处理后的三组数据由船舶运动姿态测量系统通过RS-485串口送到数据接收处理机存储、分析并实时显示船舶运动的姿态变化曲线,该数据接收处理软件采用VC++编写.经过大量试验及海上测试,该系统性能稳定,测量精度高,具有较大的实用价值.     

舰船电子元器件自主可控现状与发展需求研究

近年来,我国信息化关键软硬件技术得到了长足发展,特别是基础电子元器件性能有了大幅度提升.然而,在信息化相关的电子元器件技术和产品上与国外还存在较大差距,制约了装备的国产化率和自主可控能力水平的进一步提升.本文分析舰船装备领域基础电子元器件的发展现状,并提出下一步的发展需求建议以及确保基础电子元器件自主可控的具体措施.     

船舶机舱空气质量监测评价仪的设计及实现

机舱多模式空气质量监测评价仪是对机舱气体进行实时监测并做出评价的智能化产品.本仪器通过多种传感器对机舱气体中部分物质的含量进行采集,利用单片机进行数据整理和分析,实时给出评价.该仪器对于监测机舱环境的空气品质,为轮机人员提供自我防护决策提供了依据和保障,有较大的意义和实用价值.     

基于相关性模型的舰船系统测试性建模与分析

本文提出一种基于相关性模型的舰船系统级产品的测试性建模与分析方法.该方法通过建立产品任务模型、相关性图示模型等,利用一阶相关性列矢量法求解产品的相关性数学模型,进而建立产品诊断树和进行测试性预计,并为优化产品诊断策略提供建议.同时,根据舰用燃气轮机滑油系统组成和任务特征,建立其典型任务模型并进行精简,并在此基础上进行测试性建模、诊断树建立、测试性预计以及诊断策略优化等工作,为舰船系统级产品的测试性建模、分析和诊断策略研究提供新思路和手段.     

营运船舶航行性能和海洋环境监测平台开发验证

EEDI是衡量船舶能效水平的重要指标.由于试验条件限制,目前主要还是依靠模型试验结果对交船测试进行修正换算得到.上海船舶运输科学研究所自主研发了航行性能和海洋环境监测平台,可对营运船舶开展长期跟踪监测,实时收集船舶营运阶段的航行环境和性能参数,通过自动识别航行状态,划分海区、海况和船舶载况等因素对于船舶功率与航速的影响,可获得营运船舶实际EEDI指标,提高EEDI实船验证结果的准确性.监测平台在某万箱级集装箱船进行相关验证,并已展开长期监测.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.