基于故障树的动车组常用制动失效风险分析及对策

分析CRH3型动车组制动系统的工作原理、结构、功能及工作流程,根据其关键功能,包括空电复合制动、网络和硬线冗余指令传递、直通式电空制动方式、电气指令和空气指令传输方式等的特点,对常用制动系统结构和功能进行分解,建立常用制动失效故障树,分析基本事件的结构重要度,得出牵引执行系统电机故障、牵引控制单元故障、网压过高是导致常用制动失效发生的最重要因素,提出针对各类基本原因事件的风险控制措施.     

七阶段法在地铁信号系统风险评估中的应用

以目标距离模式ATP系统项目为基础,阐述七阶段法的风险评估应用。结合故障树分析（FTA）和事件树分析（ETA）,对目标距离模式ATP系统中的车载ATP控制单元的某个危害进行了详细的分析。     

基于决策树的水火弯板焰道点判定模型研究

目前,船体外板的制造主要是通过水火弯板工艺实现,而焰道的生成作为水火弯板工艺过程中的核心而备受关注。但由于钢材变化复杂,影响因子众多,难以得到有效的焰道。通过建立决策树模型来对钢板材料上的点进行对焰道点和非焰道点归类判定,进而得出可用于生成焰道的焰道点。实验表明,该模型对待测点的归类正确率达87.6%,能够对焰道点进行有效的判定和归类。     

A time‐staged multi‐objective network‐design model

A multi‐objective, time‐staged network‐design problem is formulated. Through transformation, the problem is decomposed into a set of single‐period, single‐objective problems. Lexicographic ordering is instrumental in effecting this transformation; it also allows a backward‐recursion algorithm to be applied using strong pruning criteria. Furthermore, monotonicity properties enable us to solve the problem using the familiar tree‐search algorithms. The solution method has several desirable properties — as shown by an example and a case study of Tripoli Province, Libya. First, the algorithm ensures continuity of project implementation over the multi time‐periods and provides optimality in later computational stages irrespective of the decision at an interim stage. Second, the algorithm tends to provide accessibility to unconnected regions in the study area at low user‐cost without employing weights to the two objective functions of accessibility and user‐cost efficiency. Such a property is deemed advantageous for suggesting transportation investments based purely on purchasing the greatest benefit for each dollar, with political neutrality strictly maintained.     

Towards comfort-optimal trajectory planning and control

ABSTRACT

This paper describes a method to analyse and evaluate different trajectory planning methods and controller types for usage in automated vehicles. Its application is shown by using a novel trajectory planning approach considering comfort aspects (based on Rapidly Exploring Random Tree (RRT)), two different controllers to follow the planned path (cascade controller and flatness based controller) and a simulation method to obtain resulting lateral vehicle accelerations. The method is used to plan and drive a trajectory through a roundabout. It can be seen that the lateral accelerations of the controller-driven vehicle are in the range of the values used for planning. However, the results of both controllers show differences in lateral deviation and in smoothness of lateral accelerations. The simulation results are then compared to real-world test drives in the same roundabout. The measured lateral accelerations are in the same range as well but show a smoother progression than the two controller models.     

事故树分析法在城市轨道交通事故分析中的应用

从系统工程学的角度出发,将广泛应用于系统安全研究中的事故树分析方法应用到城市轨道交通事故分析中。分析城市轨道交通运营事故中脱轨这一典型事故。通过分析引起列车脱轨事故各个因素,得出城市轨道交通脱轨事故的发生概率较小,预防和控制难度较大的结论。该研究有助于城市轨道交通运营公司对引起该事故发生的各个因素提高警惕意识,也为运营安全管理工作提供理论依据。     

故障树分析法在船舶主机系统故障诊断中的应用

根据故障树分析法原理,结合船舶柴油机出现的典型故障,构筑相应的故障树,从定性和定量两个方面进行分析。实践证明,故障树分析法能从故障现象着手快速判断、分析故障原因及其逻辑关系,对复杂故障的分析和故障点的定位具有较好适用性。     

数据挖掘技术在行车调整中的应用研究

在对行车调整问题进行分析的基础上,结合数据挖掘技术,采用决策树的方法,以寻找连带晚点时间总和最小的调整策略为目标,对以往积累的与运行图相关的数据资源进行分析重构,寻找各故障模式下较优的行车调整策略,并对数据挖掘模型的运行机制进行了论述。该模型在实验室中得到了应用,并取得了良好的效果。     

水下采油树树本体的加工工艺研究

根据中国南海某油气田开发项目的工况环境及应用要求,对某型卧式水下采油树关键部件——树本体制造过程中的主要技术难点进行了阐述和分析,并针对性地提出了解决措施。在此基础上,通过自主研发完成国产化试制,并按相关标准进行性能及功能测试,试验结果表明,工艺质量完全满足设计性能及功能要求。     

Exploring the feasibility of classification trees versus ordinal discrete choice models for analyzing crash severity

A cross-median crash (CMC) is one of the most severe types of crashes in which a vehicle crosses the median and sometimes collides with opposing traffic. A study of severity of CMCs in the state of Wisconsin was conducted by Lu et al. in 2010. Discrete choice models, namely ordinal logit and probit models were used to analyze factors related to the severity of CMCs. Separate models were developed for single and multi-vehicle CMCs. Although 25 different crash, roadway, and geometric variables were used, only 3 variables were found to be statistically significant which were alcohol usage, posted speed, and road conditions. The objective of this research was to explore the feasibility of GUIDE Classification Tree method to analyze the severity of CMCs to discover if any additional information could be revealed.A dataset of CMCs in the state of Wisconsin between 2001 and 2007, used in the study by Lu et al. was used to develop three different GUIDE Classification Trees. Additionally, the effects of variable types (continuous or discrete), misclassification costs, and tree pruning characteristics on models results were also explored. The results were directly compared with discrete choice models developed in the study by Lu et al. showing that the GUIDE Classification Trees revealed new variables (median width and traffic volume) that affect CMC severity and provided useful insight on the data. The results of this research suggest that the use of Classification Tree analysis should at least be considered in conjunction with regression-based crash models to better understand factors affecting crashes. Classification Tree models were able to reveal additional information about the dependent variable and offer advantages with respect to multicollinearity and variable redundancy issues.