套筒式收发球在天然气管道内检测中的应用

为解决特殊清管器和检测器以及有特殊结构收发球筒的管道难以实施内检测的问题,以某天然气管道为例,详细介绍了在多节检测器安装困难、收发球筒尺寸过短、附件安装位置不合适等限制条件下,采用套筒式收发球方式对管道进行收发球作业,安全顺利完成了管道内检测。结论认为套筒式收发球能够在不进行收发球筒改造的前提下,完成带有特殊结构收发球筒的管道内检测作业。     

基坑开挖对邻近管线的位移影响分析

隧道基坑常位于地下管线数量较多的闹市区,为避免施工过程中对周边管线的破坏,如何准确分析基坑开挖对周边管线的影响至关重要。利用三维有限元软件MIDAS GTS对基坑周边不同管线进行计算,通过对计算数据的观察分析,归纳总结基坑开挖对不同管线所造成的位移变形特点,为隧道基坑周边管线的合理保护优化提供了重要依据。     

高压供气系统设计安装问题浅析

高压气源站作为一种动力和测试气源,广泛应用在航天、航空、船舶、化工、制药等行业,具有不可替代的作用。高压气站供气系统安全正常运行的基础是设计科学,安装合理。本文在对多个高压供气系统分析总结的基础上找出了现在高压供气安装中存在的问题,分析了原因,规范了管道安装的有关工艺流程和安装测试方法。     

强噪声背景下舰船信号混沌检测方法研究

给出了舰船信号混沌检测原理,在分析Duffing方程混沌行为的基础上,给出了强噪声背景下舰船信号混沌检测模型,并分析了噪声对该混沌检测方法的影响。最后运用该混沌检测方法对舰船信号进行了数值实验,结果显示了此种方法的有效性和优越性。     

电脑智能检测系统在船舶主机上的应用

该文介绍一种智能型船舶主机电脑检测系统,该系统可以对船舶主机的性能测试中的转速、油耗、油压、水温、油温、扭矩、排温等多种物理参数进行自动采集显示.一次可同时测试多个工况.为轮机管理人员提供了检测精度高、速度快且劳动强度低的智能化设备.     

总装车间继电器安装自动化的应用

文章介绍了一种车载线束继电器安装的自动化设备,设备采用Dalta并联机器人抓取继电器进行安装,继电器上料由另一台Dalta并联机器人和视觉引导完成。继电器安装过程中,力和位移的数据被实时监控和保存,单颗继电器安装节拍满足≤1.1s,单条线束作业节拍≤45s,满足汽车总装生产线节拍要求。     

软土地层地铁隧道施工对地下管线的影响

为减小软土地层地铁隧道施工引起的地表沉降对地下管线的影响,考虑流固耦合效应和施工效应的综合作用,根据管线允许的安全控制标准,采用FLAC3D建立的数值模型,对降水、动态降水和非降水3种施工方法进行了对比研究.结果表明,非降水施工法是控制地层固结沉降最有效的施工方法.深圳地铁1号线采用该施工方法,保证了煤气管线在施工期间安全使用.     

地质雷达在上三高速公路护面墙检测中的应用

上三高速公路K224+720 ～ K225+020左山体自2008年以来,每逢大雨,该山体第二级坡面的长约20m范围内有局部泥沙从泄水孔带出,在对护面墙及碎落台的跟踪检查中,由于局限于目前管理单位的检测设备,未发现空洞、变形.为确保高速公路的安全畅通,此次采用地质雷达对该山体的护面墙进行检测,可快速了解护面墙的厚度、密实度等质量情况.     

输送成球黏土混砂土质对管线磨损的监测

吹填工程中,疏浚土对管线的磨损是工程实施的重要影响因素,目前针对成球黏土混砂土质对管线的磨损程度尚无相关研究。以厦门蔡庴工程统计数据为基础,对成球黏土混砂土质对管线磨损进行研究,分析不同部位的管线在该种土质情况下的磨损程度,并与定额中典型土质进行对比,确定出该种土质对管线的磨损,以此来指导管线的调整和优化安排。结论对类似工程有较高的指导意义,同时对管线的监测、对比、分析的方法具有普遍适用性。     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.