新型列车运行控制系统——SCBTC系统

一种基于通行信号链的列车运行控制移动闭塞系统(SCBTC-MAS),可作为一个独立监测系统与现有列车运行控制系统(TBTC或CBTC)并联运行,为列车运行提供一个"双保险"机制。SCBTC-MAS具有精确、实时的轨道占用检测及闭塞控制能力,令列车在信号系统故障、列车定位失效、人为操作错误情况下,仍可有效避免相撞事故的发生。     

基于案例推理的汽车维修专家系统

依据汽车维修行业领域的专家知识和实践经验，综合运用案例推理、模糊推理和缺省推理等方法，对汽车维修中的多种故障采取原因和症状相结合的维修思路进行推理机制的设置，建立基于案例推理、模糊推理和缺省推理相结合的、能迅速确定汽车维修方案的推理模型，建立了某企业汽车维修系统的原型系统。     

运用经济杠杆长效治理超载超限运输

分析了经济利益贯穿的货主—运输业户—车辆生产、改装厂家的超载超限运输链条的成因、现状和危害;提出了要从以核定载质量为依据转而以货车实际总重和轴载限额为依据对货车实施计重收费的思路,通过区别对待,体现公平,分步推进,累积治理,实现运用经济杠杆,达到长效治理超载超限运输的目的;阐述了江苏、河南、青海等省份实行计重收费所产生的积极效果以及他们推广的安排;提出在计重收费方法以及低速动态轴载称重设备精度、可靠度和价格方面还需要进一步探讨。     

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。     

Identifying tourists and analyzing spatial patterns of their destinations from location-based social media data

Reliable travel behavior data is a prerequisite for transportation planning process. In large tourism dependent cities, tourists are the most dynamic population group whose size and travel choices remain unknown to planners. Traditional travel surveys generally observe resident travel behavior and rarely target tourists. Ubiquitous uses of social media platforms in smartphones have created a tremendous opportunity to gather digital traces of tourists at a large scale. In this paper, we present a framework on how to use location-based data from social media to gather and analyze travel behavior of tourists. We have collected data of about 67,000 users from Twitter using its search interface for Florida. We first propose several filtering steps to create a reliable sample from the collected Twitter data. An ensemble classification technique is proposed to classify tourists and residents from user coordinates. The accuracy of the proposed classifier has been compared against the state-of-the-art classification methods. Finally, different clustering methods have been used to find the spatial patterns of destination choices of tourists. Promising results have been found from the output clusters as they reveal most popular tourist spots as well as some of the emerging tourist attractions in Florida. Performance of the proposed clustering techniques has been assessed using internal clustering validation indices. We have analyzed temporal patterns of tourist and resident activities to validate the classification of the users in two separate groups of tourists and residents. Proposed filtering, identification, and clustering techniques will be significantly useful for building individual-level tourist travel demand models from social media data.     

Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide.     

美国可变船型气垫船(T-Craft)技术方案

美国海军研究署(ONR)2006年启动可变船型气垫船(Transformable Craft,简称:T-Craft)项目,用于海上基地的高速连接舰。第一阶段研究主要开展初步方案论证及技术风险分析等;第二阶段研究自2008年初开始,包括关键技术研究、方案设计和模型试验等。文章主要介绍在合同第二阶段,Alion公司及TMLS公司对该船型的一些研究工作和关键技术解决方案。     

盾构隧道EPDM橡胶密封垫本构参数试验研究

为合理确定盾构隧道接缝EPDM弹性密封垫橡胶材料的本构模型及其参数,采用CMT4304型微机控制电子万能试验机,进行单轴拉伸试验和单轴压缩试验,并利用ABAQUS有限元分析软件对试验数据进行分析,从模型符合性和材料稳定性2方面进行评价,得出常用硬度EPDM橡胶材料的推荐本构模型及其参数。结果表明:邵尔硬度为45 HA和60 HA的EPDM橡胶,采用Arruda-Boyce或van der Waals本构模型较合适;邵尔硬度为55 HA的EPDM橡胶,采用Arruda-Boyce或Yeoh本构模型较合适;邵尔硬度为65 HA的EPDM橡胶,采用Mooeny-Rivlin本构模型较合适。     

A signal-based fault detection and classification method for heavy haul wagons

This paper proposes a signal-based fault detection and isolation (FDI) system for heavy haul wagons considering the special requirements of low cost and robustness. The sensor network of the proposed system consists of just two accelerometers mounted on the front left and rear right of the carbody. Seven fault indicators (FIs) are proposed based on the cross-correlation analyses of the sensor-collected acceleration signals. Bolster spring fault conditions are focused on in this paper, including two different levels (small faults and moderate faults) and two locations (faults in the left and right bolster springs of the first bogie). A fully detailed dynamic model of a typical 40t axle load heavy haul wagon is developed to evaluate the deterioration of dynamic behaviour under proposed fault conditions and demonstrate the detectability of the proposed FDI method. Even though the fault conditions considered in this paper did not deteriorate the wagon dynamic behaviour dramatically, the proposed FIs show great sensitivity to the bolster spring faults. The most effective and efficient FIs are chosen for fault detection and classification. Analysis results indicate that it is possible to detect changes in bolster stiffness of ±25% and identify the fault location.     

基于灰色残差GM（1，1）模型的道路交通量预测的研究

道路交通体系是一个多因素、多层次、多目标的复杂系统。其中交通量信息系统具有明显的层次复杂性,结构关系的模糊性,动态变化的随机性,指标数据的不完全和不确定性。由于技术方法、人为因素、自然环境变化的影响,造成各种数据误差、短缺甚至虚假现象,系统的作用机制不明确,系统的状态、结构、边界关系难以精确描述,属于典型的灰色系统。在作量化、模型化、实体化研究时,能作为反映系统主要动态特征的数据是很少的。由于环境对系统的干扰,系统信息中原始数据序列往往呈现离乱情况,离乱数列即为灰色数列或称灰色过程,灰色理论利用那些较少的或不确切的表示系统行为特征的原始数据序列作生成变换后建立微分方程,对灰色过程建立的模型称为灰色模型（Greymodel）,简称GM模型。本文从理论上介绍了GM（1,1）模型和灰色残差GM（1,1）模型建立的一般过程,然后将其应用于交通量预测的实际例子中。预测结果表明,该方法是可行的。