城市轨道交通信号系统信息安全风险辨识

从城市轨道交通信息安全面临的严峻形势出发,介绍城轨交通信号系统组成,并对信号系统各子系统功能进行阐述。城轨交通信号系统是保证列车安全、准点、高密度运行的重要技术装备,主要由列车自动监控子系统、列车自动防护子系统、列车自动运行子系统、联锁子系统组成。根据信息安全风险分析模型,识别城轨交通信号系统信息安全的威胁来源及核心资产。由于城轨交通系统属于工业控制系统的典型系统,城轨信号系统则具备工控系统的一般性特点,继承工控系统的脆弱性。针对国内城轨交通信息安全研究的空白之处,结合工控系统不同层级结构的脆弱性,从技术和管理两个方面进行信号系统的信息安全风险辨识,通过分析发现存在物理安全、网络安全、主机安全和应用安全等层次上的风险。风险辨识结果反映出城轨交通信息安全存在大量的薄弱环节,以期为日后的研究和防护工作的开展打下基础。     

公私合作模式下城市轨道交通项目风险识别研究

在PPP模式风险研究和城市轨道交通PPP项目特点研究的基础上,按照项目风险水平程度将城市轨道交通PPP项目风险划分为宏观、中观和微观3个等级,再采用德尔菲法和核对表法,识别出PPP模式下城市轨道交通项目的77个风险因素。     

图像测量技术在汽车轴距差检测中的应用研究

通过采集汽车直行中轮胎印迹图像 ,利用偏差相对测量法 ,即先测出汽车单轴的偏斜量 ,然后计算出汽车轴距左右差。通过开发的检测系统进行试验 ,结果表明 ,检测精度满足汽车轴距左右差在线检测要求。     

BP和RBF神经网络在辨识内燃机燃烧过程中的应用

分析了发动机燃烧过程的研究方式,提出了用BP和RBF网络辨识内燃机燃烧过程的方法。选定神经网络的结构、隐层神经元的作用函数和控制参数,成功地得到了发动机的辨识模型,结果由RBF网络辨识的模型给出,从这一模型可以获得任意点缸内压力和温度以延拓的参数,为排放分析、计算和结构优化提供了良好的基础。     

客车主要噪声源识别的试验研究

基于偏奇异值分析法识别噪声源的基本原理，采用了近场声压测量法，同步采集15个传感器的振动与声压信号，识别出客车车外噪声的主要噪声源，分析出各噪声源对车外噪声的贡献并做出降低车外噪声的预测分析。所采用的试验与分析方法具有计算量小、声源定位准确的特点，并且可以准确预测零部件的改进对车外噪声的影响。试验研究和实车应用表明，这种方法可以适用于复杂的工程实际。     

公路交通可持续发展评价指标及评价方法研究

根据公路交通可持续发展评价的内容和特点,从公路交通可持续发展水平、发展能力、发展协调性3个方面建立了评价指标体系;提出了指标属性值和无量纲化的计算方法;应用模糊识别原理,结合AHP权重确定方法,依据公路交通可持续发展目标(级别划分)的实现程度,提出公路交通可持续发展的多级模糊识别综合评价模型;其评价方法和模型,反映了公路交通可持续发展的内涵,对区域公路交通可持续发展评价有借鉴作用。最后,进行了实证研究。     

The impact of the Polar Code on risk mitigation in Arctic waters: a “toolbox” for underwriters?

The existing risk weighing on vessel, crew and ecosystem in the Arctic and more globally in Polar waters promoted the adoption of the Polar Code (PC) early 2017, a mandatory international legal framework intended for enhanced safety and environmental protection. While the substance of the PC has been extensively analyzed, few studies have focused on the underlying relationships between the PC and underwriters. Based on an extensive literature review, documentary materials and interviews with insurance companies, this article conceptualizes the PC as a “toolbox” and analyzes how underwriters can exploit it in their work within the emerging Arctic market. The PC does not only regulate the navigation in Arctic waters in legal terms, but is also aimed at mitigating risks in the Polar areas through the identification of hazard sources and proceduralization of risk assessment. As a result we observe a certain “Polar Code paradox”. Even though the PC is a risk-based instrument and constitutes a key step for improving ship insurability, it has only limited capacity to assist underwriters in assessing risks and insuring vessels. Marine insurers still face a lack of data and high pending uncertainties leading them to exercise extreme caution with Arctic risks appraisal.     

隧道爆炸冲击波的危害及控制措施

目前山岭隧道施工基本以钻爆法为主,爆破过程中产生的冲击波会对隧道内的人员及机械设备安全产生较大影响,造成重大安全事故和财产损失。本文主要介绍了冲击波在隧道内传播会形成超压,且随着传播距离增加超压峰值逐渐衰减到大气压范围内;基于超压准则评估了冲击波对人体、隧道内设施及周边建筑物的危害程度;通过在隧道内安装简易的冲击波缓冲装置及加强监测、设置安全警戒线等控制措施,减弱了爆破冲击波的危害,从而达到安全快速施工的目的。     

Detection of nonlinearity effects in structural integrity monitoring methods for offshore jacket-type structures based on principal component analysis

The detection of changes in the dynamic behavior of structures is an important issue in structural safety assessment. The development of detection methods assumes greater significance in the case of offshore platforms because the inherent problems are compounded by the harsh environment. Here, we describe an instrumented physical model for the structural health monitoring of an offshore jacket-type structure and the results of tests in several different damage scenarios. In a comparative investigation of two different methods, we discuss the difficulties of implementing damage detection techniques for complex structures, such as offshore platforms. The combined algorithm of a fuzzy logic system and a model updating method are briefly discussed, and a method based on stochastic autoregressive moving average with exogenous input is adopted for the structure. The consideration of uncertainties and the effects of nonlinearity were major objectives. So, the methods were also investigated based on the test scenarios consisting of the physical model with a geometric nonlinearity. The principal component analysis method was utilized for the detection of nonlinearity in the recorded data. The results show that the developed methods are suitable for damage classification, but the quality of the acquired signals must be considered an important factor influencing successful classification. The development of these methods may be extremely useful, as such technologies could be applied for offshore platforms in service, enabling damage detection with fewer false alarms.     

Plate scanning tools to obtain travel times in traffic networks

The management of vehicle travel times has been shown to be fundamental to traffic network analysis. To collect travel time measurement, some methods focus solely on isolated links or highway segments, and where two measurement points, at the beginning and at the end of a section, are deemed sufficient to evaluate users' travel time. However, in many cases, transport studies involve networks in which the problem is more complex. This article takes advantage of the plate scanning technique to propose an algorithm that minimizes the required number of registering devices and their location in order to identify vehicles candidates to compute the travel times of a given set of routes (or subroutes). The merits of the proposed method are explained using simple examples and are illustrated by its application to the real network of Ciudad Real.