DCM船施工钻杆冲洗水泵随机启动器系统的设计

本文将结合船舶水泵的工作原理,对船舶水泵的运行情况进行分析,详细介绍以单片机为核心的钻杆冲洗水泵随机启动器系统的设计。同时通过搭建Proteus仿真模型,针对钻杆附着淤泥的不同程度对船舶水泵进行动态模拟。本文将着重介绍DCM钻杆冲洗中船舶多水泵随机启动器系统的设计。     

复杂艰险山区高速铁路减灾选线设计研究

复杂艰险山区地质灾害问题十分突出,工程建设条件差,高速铁路线型标准高,适应地形及绕避不良地质的灵活性差。对于长达数百至上千公里的复杂艰险山区高速铁路带状工程,众多的地质灾害绕无可绕、避无可避时,只能避大就小,海量筛选技术可行、经济合理、风险可控的线路和工程方案。高效识别“长线路、宽廊道”范围地质灾害,量化百年服役期铁路工程安全风险,科学确定“宏观走向”“空间线位”“工程设置”等多层次风险调控举措,实现以“减灾”为核心的方案群多目标智能优化,是复杂艰险山区高速铁路成功修建与安全运营的关键。本文简介了复杂艰险山区高速铁路减灾选线设计成套技术,该技术以“一套减灾选线理论与方法”+“三大减灾选线支撑技术”为核心,成功突破了复杂艰险山区修建高速铁路的技术瓶颈,支撑了6300 km复杂艰险山区高速铁路的工程建设,指导了1.3万km高速铁路的勘察设计,并被其他陆地交通项目借鉴利用,在服务“交通强国”战略、“一带一路”建设中具有重大意义并具有广阔应用前景。     

基于信号和车辆系统联控的弓靴转换控制设计研究

广州地铁4号、5号、6号、14号、21号线运营线路采用第三轨集电靴受流方式,车辆段采用接触网受电弓受流方式,列车在进出车辆段时,需在弓靴转换点处进行降弓升靴或降靴升弓的操作,传统人防监控方法是人工监控与视频监控。文章研究利用信号定位、车辆控制软件联控的方式,实现列车弓靴转换由人防向技防的转变,设计研究成果已在广州地铁14号、21号线车辆段出入段线弓靴转换点处成熟应用。该设计研究方案能优化列车出入场管理、节约人力资源,并从根本上解决人工未按要求进行弓靴转换而产生的安全风险。     

GSM-R中跨SGSN更新时源SGSN域名解析数据的智能生成方案设计

源SGSN域名解析数据是GSM-R网络编号方案数据中重要的需跨局制作的一类数据。由RAI编码构造生成,在跨SGSN路由区更新时,存储于DNS中,以解析源SGSN的IP地址。全路400多条G网线路,错综复杂的基站引用关系,导致数据复杂多样。针对该情况,利用聚类分析和关联规则分析算法,研究源SGSN解析数据的智能生成方案,提高数据的全面性、准确性,从而有效保障GSM-R分组域应用业务的正常运转。     

Electric vehicles and residential parking in an urban environment: Results from a stated preference experiment

This paper presents the results of a preference survey of 1545 respondents’ willingness to purchase electric vehicles (EVs) in Philadelphia. We pay particular attention to respondents’ willingness to pay for convenient charging systems and parking spaces. If the value of dedicated parking substantially outweighs the value of convenient charging systems, residential-based on-street charging systems are unlikely to ever be politically palatable. As expected, respondents are generally willing to pay for longer range, shorter charging times, lower operating costs, and shorter parking search times. For a typical respondent, a $100 per month parking charge decreases the odds of purchasing an EV by around 65%. Across mixed logit and latent class models, we find substantial variation in the willingness to pay for EV range, charge time, and ease of parking. Of note, we find two primary classes of respondents with substantially different EV preferences. The first class tends to live in multifamily housing units in central parts of the city and puts a high value on parking search time and the availability of on-street charging stations. The second class, whose members are likelier to be married, wealthy, conservative, and residing in single-family homes in more distant neighborhoods, are willing to pay more for EV range and charge time, but less for parking than the first group. They are also much likelier to consider purchasing EVs at all. We recommend that future research into EV adoption incorporate neighborhood-level features, like parking availability and average trip distances, which vary by neighborhood and almost certainly influence EV adoption.     

Joint deployment of charging stations and photovoltaic power plants for electric vehicles

The focus of this study is to jointly design charging stations and photovoltaic (PV) power plants with time-dependent charging fee, to improve the management of the coupled transportation and power systems. We first propose an efficient and extended label-setting algorithm to solve the EV joint routing and charging problem that considers recharging amount choices at different stations and loop movement cases. Then, a variational inequality problem is formulated to model the equilibrium of EV traffic on transportation networks, and an optimal power flow model is proposed to model the power network flow with PV power plants and optimally serve the EV charging requirements. Based on the above models for describing system states, we then formulate a model to simultaneously design charging stations, PV plants, and time-dependent charging fee. A surrogate-based optimization (SBO) algorithm is adopted to solve the model. Numerical examples demonstrate that the proposed SBO algorithm performs well. Additionally, important insights concerning the infrastructure design and price management of the coupled transportation and power networks are derived accordingly.     

电动汽车充电桩安全管理研究

随着国家对环境保护和能源节约的重视以及新能源政策的实施,电动汽车行业迎来了快速发展。充电基础设施的建设,是加快电动汽车推广的重要需要。电动汽车充电基础设施建设和运营业务发展的机会也极大,随之而来的安全管理工作要求也越来越高。本文依据充电桩建设和运营的特点,剖析其中面临的安全风险,并提出加强安全管理工作的措施,为充电桩企业安全管理运营提供参考和借鉴。     

基于深度强化学习的智能船舶航迹跟踪控制

[目的]智能船舶的航迹跟踪控制问题往往面临着控制环境复杂、控制器稳定性不高以及大量的算法计算等问题。为实现对航迹跟踪的精准控制,提出一种引入深度强化学习技术的航向控制器。[方法]首先,结合视线(LOS)算法制导,以船舶的操纵特性和控制要求为基础,将航迹跟踪问题建模成马尔可夫决策过程,设计其状态空间、动作空间、奖励函数;然后,使用深度确定性策略梯度(DDPG)算法作为控制器的实现,采用离线学习方法对控制器进行训练;最后,将训练完成的控制器与BP-PID控制器进行对比研究,分析控制效果。[结果]仿真结果表明,设计的深度强化学习控制器可以从训练学习过程中快速收敛达到控制要求,训练后的网络与BP-PID控制器相比跟踪迅速,具有偏航误差小、舵角变化频率小等优点。[结论]研究成果可为智能船舶航迹跟踪控制提供参考。     

动车组单车调试工艺及发展趋势

对动车组传统单车调试工艺进行了总结对比,阐述了以智能调试系统、数字化平台为基础的自动化调试原理.重点介绍了智能单车调试设备、智能端部模拟器和移动控制终端,分析了单车智能调试技术的发展趋势.     

船舶甲板智能抛丸机器人设计

为解决在船舶外场涂装阶段除锈和拉毛施工效率低、质量不稳定、环境污染严重等问题,设计一款用于船舶甲板的智能抛丸机器人。简介该型机器人系统组成,阐述其抛丸分系统、除尘分系统和越障辅助机构的硬件设计及其软件设计,并设计手动遥控和自主导引操作方式。实船测试结果表明,该型机器人可满足船舶甲板除锈清理的工作要求。