面向国产大型邮轮的虚拟设计评审方案研究

本文分析了国内大型邮轮三维设计模型的虚拟评审需求,基于Intergraph Smart 3D和SmartPlant Review软件,提出了国产大型邮轮虚拟设计评审的总体解决方案。该方案采用三维模型轻量化、模型虚拟评审以及大型邮轮设计-评审数据转换等关键技术,实现了面向大型邮轮设计的沉浸式三维模型全流程虚拟评审,并通过在国产大型邮轮设计模型上的应用测试,验证了该方案的可行性,可为提高大型邮轮设计生产效率、缩短建造周期以及降低生产成本等提供重要的技术支撑。     

智能网联车辆交通信息处理技术与信号控制方法研究

随着科学技术的不断加强,智能网联车辆的数量也在不断增加,在智能交通系统发展中,车联网发挥了重要作用,人们对于车联网的研究也越来越多和越来越深入,为了能够使车联网更好的普及,应该加强对智能网联车辆交通信息技术和信号控制的研究。本文基于目前车联网发展现状对智能网联车辆信息处理技术和信号控制的方法进行探讨研究,以供参考。     

基于Halcon及VS的动车组制动闸片厚度自动识别模块

研究基于图像处理和模式识别的动车组闸片厚度自动识别模块,解决动车组制动时因闸片过薄而导致的车轮迅速升温,甚至引发不安全状态的问题。该模块可实现动车组通过时自动检测,即自动拼图、图像预处理、模型定位及制动闸片厚度计算,并对厚度小于一定数值的闸片进行自动报警。通过大量实验和测试表明,该模块可以有效地计算闸片的厚度,具有很好的鲁棒性。     

公路工程钢筋区域化集中加工发展模式分析

首先分析了公路工程建设模式的发展趋势对钢筋加工的新需求,提出可采用区域化集中加工的公路工程钢筋加工发展模式。结合对典型施工单位的调研,进行了现有公路工程现有钢筋加工厂有效生产时间、有效生产时间内钢筋加工厂的生产能力情况、钢筋加工厂用地指标、钢筋加工厂用电能耗指标、钢筋加工厂其他能耗指标等方面的调研。从调研结果可见,区域化钢筋集中加工存在比各标段自建钢筋加工厂的合理性,在条件适宜的前提下,将各标段自建钢筋加工厂转化为区域化钢筋集中加工厂是合理、可行的。在此基础上,探讨了公路工程区域性钢筋集中加工的主要实施模式以及各模式的特点及优势。     

高职高专中药炮制技术课程数字化教学资源的构建与运用——以郑州铁路职业技术学院中药专业为例

数字化信息化教学模式已经逐渐发展为高职高专教学的主流,为了适应数字化信息化教学模式的变化,郑州铁路职业技术学院依托信息化教学平台,通过构建中药炮制技术课程数字化资源,建设了微课、PPT、在线题库等数字资源,以线上线下相结合的混合教学模式,激发了学生学习的积极性和热情,丰富并提高了师生互动的方式和频率,达到了提高教学质量的目的。     

LNG运输船BOG处理技术发展与演化路径研究

LNG运输船具有良好的发展前景，BOG的妥善处理是LNG燃料运输船安全航行的重要环节。通过专利数据挖掘与数据分析技术，归纳全球LNG运输船BOG处理领域的焦点技术和前沿技术，并且结合专利文本信息梳理出BOG处理技术的演化路径。研究结果发现，BOG处理领域内专利申请集中在回收利用方式、再液化装置及再液化处理方式三个方面。企业在今后发展中应针对涡轮布雷顿制冷技术进行重点研发和专利布局。     

公路工程试验检测数据处理问题探析

在公路工程的施工技术管理中,工程试验检测是一个重要环节,同时也是公路施工质量控制和工程竣工验收工作中不可或缺的一个关键步骤。针对这样一个关键环节,从数据表达和误差表示两个方面分析公路工程试验检测数据处理问题,可供参考借鉴。     

Virtual 3D city model as a priori information source for vehicle localization system

This paper aims at demonstrating the usefulness of integrating virtual 3D models in vehicle localization systems. Usually, vehicle localization algorithms are based on multi-sensor data fusion. Global Navigation Satellite Systems GNSS, as Global Positioning System GPS, are used to provide measurements of the geographic location. Nevertheless, GNSS solutions suffer from signal attenuation and masking, multipath phenomena and lack of visibility, especially in urban areas. That leads to degradation or even a total loss of the positioning information and then unsatisfactory performances. Dead-reckoning and inertial sensors are then often added to back up GPS in case of inaccurate or unavailable measurements or if high frequency location estimation is required. However, the dead-reckoning localization may drift in the long term due to error accumulation. To back up GPS and compensate the drift of the dead reckoning sensors based localization, two approaches integrating a virtual 3D model are proposed in registered with respect to the scene perceived by an on-board sensor. From the real/virtual scenes matching, the transformation (rotation and translation) between the real sensor and the virtual sensor (whose position and orientation are known) can be computed. These two approaches lead to determine the pose of the real sensor embedded on the vehicle. In the first approach, the considered perception sensor is a camera and in the second approach, it is a laser scanner. The first approach is based on image matching between the virtual image extracted from the 3D city model and the real image acquired by the camera. The two major parts are: 1. Detection and matching of feature points in real and virtual images (three features points are compared: Harris corner detector, SIFT and SURF). 2. Pose computation using POSIT algorithm. The second approach is based on the on–board horizontal laser scanner that provides a set of distances between it and the environment. This set of distances is matched with depth information (virtual laser scan data), provided by the virtual 3D city model. The pose estimation provided by these two approaches can be integrated in data fusion formalism. In this paper the result of the first approach is integrated in IMM UKF data fusion formalism. Experimental results obtained using real data illustrate the feasibility and the performances of the proposed approaches.     

From Twitter to detector: Real-time traffic incident detection using social media data

The effectiveness of traditional incident detection is often limited by sparse sensor coverage, and reporting incidents to emergency response systems is labor-intensive. We propose to mine tweet texts to extract incident information on both highways and arterials as an efficient and cost-effective alternative to existing data sources. This paper presents a methodology to crawl, process and filter tweets that are accessible by the public for free. Tweets are acquired from Twitter using the REST API in real time. The process of adaptive data acquisition establishes a dictionary of important keywords and their combinations that can imply traffic incidents (TI). A tweet is then mapped into a high dimensional binary vector in a feature space formed by the dictionary, and classified into either TI related or not. All the TI tweets are then geocoded to determine their locations, and further classified into one of the five incident categories.We apply the methodology in two regions, the Pittsburgh and Philadelphia Metropolitan Areas. Overall, mining tweets holds great potentials to complement existing traffic incident data in a very cheap way. A small sample of tweets acquired from the Twitter API cover most of the incidents reported in the existing data set, and additional incidents can be identified through analyzing tweets text. Twitter also provides ample additional information with a reasonable coverage on arterials. A tweet that is related to TI and geocodable accounts for approximately 5% of all the acquired tweets. Of those geocodable TI tweets, 60–70% are posted by influential users (IU), namely public Twitter accounts mostly owned by public agencies and media, while the rest is contributed by individual users. There is more incident information provided by Twitter on weekends than on weekdays. Within the same day, both individuals and IUs tend to report incidents more frequently during the day time than at night, especially during traffic peak hours. Individual tweets are more likely to report incidents near the center of a city, and the volume of information significantly decays outwards from the center.     

智慧高速公路设计案例分析

本文以某智慧高速的设计案例为依托,首先对国内外智慧高速发展和应用现状进行归纳总结,分析认为电动化、智能化的新型运载工具,信息化和功能专业化的基础设施,开放、共享、协同的管理与服务将是未来高速公路三大发展趋势。通过对高速公路使用者和管理者的需求针对性地精准分析,构建面向高速公路使用者和管理者的创新型应用服务。结合新技术的发展趋势,以服务需求为导向,建设"三网合一"智慧高速基础设施和智慧云控平台构成、数据流为驱动的、"开放、包容、创新"的智慧高速公路。基于案例分析的智慧高速规划设计全过程,对于国内智慧高速的整体设计和建设规划具有重要参考价值,探索开辟全新的高速公路智能化建设方向和思路。