有线载波技术在汽车数据传输中的应用研究

研究了有线载波技术在汽车数据传输中的应用，通过汽车内的电力线同时实现了供电以及数据的安全传输。     

基于复合神经网络模型的四轮独立驱动电动车控制

针对四轮独立驱动电动车的运动控制，提出了一种基于Ackerman转向模型和神经网络方法的复合模型，用于对各个车轮转速进行仿真和控制。这种复合模型的特点是结构非常精简，其参数可用实际整车数据来直接整定，尤其适合于车辆的中低速运行控制。     

以位移为基础的钢筋混凝土连续梁桥抗震设计方法

利用等效线性化方法将钢筋混凝土(RC)连续梁桥结构简化为多自由度线弹性体系,采用振型反应谱的概念研究了结构在横向地震作用下考虑多阶模态效应的直接基于位移的抗震设计方法。探讨了连续梁桥的上部结构(主梁)及桥墩(台)刚度的变化对结构横向振动模态质量与模态周期的影响,给出了多阶模态设计方法的具体设计过程。对对称与非对称连续梁桥采用相同的设计步骤进行基于位移的抗震设计,并对设计算例用非线性时程分析验证了设计结果的合理性。     

赣江大桥公路桥病害检测与安全评估

首先对赣江大桥公路桥进行病害调查,评定全桥各部位损伤状态。根据评定结果,再对材料退化、结构损伤与受力性能进行实桥测试。应用断裂力学方法,采用观测和超声波探测方法确定初始裂纹尺寸,通过裂纹扩展模拟得出临界杆件的剩余寿命。综合实测数据与理论分析,评估该桥使用安全性和剩余寿命,并建议维护加固措施。     

磁导航车体运动数字控制系统数学模型研究

探讨磁导航车体运动数字控制系统的数学模型。用实验方法建立磁导航车体运动数字控制系统典型环节的时间连续数学模型,结合车体运动机械操纵环节的传统数学模型建立整个控制系统的时间连续数学模型。利用Z变换方法把控制系统时间连续数学模型转换成离散数学模型,引入数字控制系统典型环节的数学模型,建立磁导航车体运动数字控制系统的离散数学模型。设计数字控制系统的二次型最优控制器并进行计算机仿真。仿真分析结果验证了数学模型的有效性。     

挖掘机电子控制系统(Ⅰ)

简述小松、大宇等挖掘机电子控制系统、电子功率优化系统和工作模式控制系统,介绍自动怠速装置的原理及故障诊断,详细论述电子油门和发动机电子控制系统工作原理及故障诊断。     

意大利威尼斯集装箱深水港投资模式分析

全球经济回暖以及"一带一路"倡议给中资企业参与海外港口投资提供了良好契机,但海外港口投资也存在政治、经济、文化等多方面的风险。针对目前中资企业海外港口投资中存在的问题,系统分析中资企业海外港口投资模式及其优劣和适用情况,并结合国外主要港口管理模式,以意大利威尼斯集装箱深水港投资实践为典型案例,提出海外港口投资策略。     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

机器人生产线在船舶智能制造中的应用研究

智能制造是“中国制造2025”的主攻方向。本文先浅谈了智能船厂，并结合国内首个智能船厂试点对智能船厂的初级发展建设等进行初步探索，主要对船舶智能制造机器人生产线应用进行梳理分析，如工艺流程及布置、生产模式改进、提质增效和人员减配等。     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.