船用电子设备现场可靠性维修性数据分析的需求与方法

从分析船用电子设备现场可靠性数据收集和分析处理工作的概念、方法和目的入手，明确了现场数据收集的主要内容，从定性和定量的角度，阐述了现场数据分析处理和利用的主要方法和步骤，并对部分维修决策参数的计算方法进行了探讨。     

舰船通信安全保密研究

分析和探讨了舰船通信安全保密背景、美海军安全保密动态以及舰船通信安全保密特点,提出了舰船通信安全保密使命任务以及舰船通信安全保密的技术框架.     

战术数据链技术的发展趋势

根据未来信息化战争对战术数据链网络的需求,从多网结构、自适应能力、频段、高阶、宽带调制、一体化、抗电磁干扰、软件无线电结构、应用扩展和安全保密等方面论述了战术数据链技术的发展趋势.     

模块化数据采集和显示报警系统

用PLC、单片微机和IPC组成的模块化数据采集和显示报警系统，将现代自动化控制的主要技术优化组合起来，具有开发周期短、可靠性高、功能强、成本低，故障修复快，可扩展性好等特点，虹桥机场油库的数据采集和显示报警系统就是这类系统的一个实例。     

一种高效的Ad Hoc网络链路层数据级联方法

在Ad Hoc网络条件下,受接入层效率及高误码率等客观因素影响,链路层传输性能较低。针对这一问题,提出了一种高效的链路层数据级联方法,使发端的数据既能更好地匹配接入层协议,得到较高的吞吐量,又能减少高误码率对传输性能的影响。理论及仿真结果表明：与传统的数据级联方法相比,该方法可获得更高的链路层吞吐量,提升了Ad Hoc网络链路层的传输性能。     

Short-term speed predictions exploiting big data on large urban road networks

Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the road network and provide great opportunities for enhanced short-term traffic predictions based on real-time information on the whole network. Two network-based machine learning models, a Bayesian network and a neural network, are formulated with a double star framework that reflects time and space correlation among traffic variables and because of its modular structure is suitable for an automatic implementation on large road networks. Among different mono-dimensional time-series models, a seasonal autoregressive moving average model (SARMA) is selected for comparison. The time-series model is also used in a hybrid modeling framework to provide the Bayesian network with an a priori estimation of the predicted speed, which is then corrected exploiting the information collected on other links. A large floating car data set on a sub-area of the road network of Rome is used for validation. To account for the variable accuracy of the speed estimated from floating car data, a new error indicator is introduced that relates accuracy of prediction to accuracy of measure. Validation results highlighted that the spatial architecture of the Bayesian network is advantageous in standard conditions, where a priori knowledge is more significant, while mono-dimensional time series revealed to be more valuable in the few cases of non-recurrent congestion conditions observed in the data set. The results obtained suggested introducing a supervisor framework that selects the most suitable prediction depending on the detected traffic regimes.     

山区农村公路安全保障工程应用技术研究

在对山区农村公路广泛调研的基础上,针对事故多发路段,运用具有山区农村公路特色的安全保障技术,对不同危险路段综合安全保障工程的应用进行论述,提出相应的安全保障工程改善对策。     

Mining missing train logs from Smart Card data

This paper shows how to recover the arrival times of trains from the gate times of metro passengers from Smart Card data. Such technique is essential when a log, the set of records indicating the actual arrival and departure time of each bus or train at each station and also a critical component in reliability analysis of a transportation system, is missing partially or entirely. The procedure reconstructs each train as a sequence of the earliest exit times, called S-epochs, among its alighting passengers at each stations. The procedure first constructs a set of passengers, also known as reference passengers, whose routing choices are easily identifiable. The procedure then computes, from the exit times of the reference passengers, a set of tentative S-epochs based on a detection measure whose validity relies on an extreme-value characteristic of the platform-to-gate movement of alighting passengers. The tentative S-epochs are then finalized to be a true one, or rejected, based on their consistencies with bounds and/or interpolation from prescribed S-epochs of adjacent trains and stations. Tested on 12 daily sets of trains, with varying degrees of missing logs, from three entire metro lines, the method restored the arrival times of 95% of trains within the error of 24 s even when 100% of logs was missing. The mining procedure can also be applied to trains operating under special strategies such as short-turning and skip-stop. The recovered log seems precise enough for the current reliability analysis performed by the city of Seoul.     

铁道车辆轴箱弹簧断裂故障对动力学性能的影响

车辆运行过程中,当轴箱弹簧突发断裂故障,会造成动力学状态和性能突变,一系悬挂刚度突然减小,暂时失去承载能力,会威胁车辆行车安全。结合整车的动力学仿真,建立了轴箱弹簧断裂过程的力学模型,对整个断裂过程进行仿真,模拟了轴箱弹簧突然断裂工况下车辆动力学性能变化,分析了轴箱弹簧断裂条件下车辆直线行车安全性以及曲线通过安全性。计算分析结果表明:轴箱弹簧突然断裂导致一系悬挂刚度剧变,引起轮轨垂向力先减小后增大,轮重减载率、脱轨系数等参数增大直至超限,但对轮轨横向力影响不大。     

道路桥梁检测数据结合BIM技术的应用研究

随着市政道路桥梁检测要求的不断提高,检测数据分析和应用深度也随之提高,如何让检测数据更加有效、更加生动的反应道路桥梁的技术状况,成为了越来越多使用单位的基本诉求.针对这一现象,论文介绍了道路桥梁检测数据与BIM技术结合的基本路径,分析阐述了道路桥梁检测数据的主要内容及应用方面的不足,重点研究了如何以BIM信息模型作为检测数据载体的实施方法,归纳了哪些检测数据更加迫切的需要导入到BIM模型中,并通过分析各方单位的不同需求,对使用BIM模型中检测数据的应用场景提出了实施方案,为BIM信息模型的建设和应用提供了新的思路.