高速铁路光回路异物侵限监测系统方案研究

为了解决高速铁路异物侵限双电网监测系统存在的抗干扰能力差,双电网需连续稳定供电、工程投资大等问题,运用光纤通信、计算机网络和自动控制等技术,提出光回路异物侵限监测系统的方案,论述系统构成方案,检知网的设计方案,传感光纤的选型、敷设方式和接续方案,光信号衰耗指标的计算以及监控单元、铁路局中心系统设置方案等内容,有效解决双电网监测系统存在的问题,对保障高速铁路运输安全具有一定价值。     

高速铁路异物侵限监测网设置范围计算公式的完善

高速铁路异物侵限监测系统是高速铁路重要的基础设施,其监测网的安装范围正确与否将直接关系到高速铁路的运输安全,原铁道部运输局2010年颁布的《高速铁路防灾安全监控系统-公跨铁立交桥异物侵限监测方案》提供了公跨铁立交桥异物侵限监测电网设置范围的计算公式。通过举例分析发现,当公跨铁立交桥与铁路线的夹角大于70°时,该计算公式得出的计算结果偏小,甚至还会出现负值的不合理现象,对高速铁路运营安全产生不利影响,因此有必要对该计算公式进行修改完善。根据公跨铁立交桥与铁路线的夹角大小分(0,70°)、[70°,90°)、[90°,180°)三个区间进行讨论,并利用三角函数法,研究得出一整套新的计算公式。研究成果表明,用新的计算公式得出的公跨铁立交桥异物侵限监测电网设置范围更加科学合理,提高了高速铁路异物侵限监测系统的安全监控性能。     

高速公路大坪滑坡深部监测动态特征分析

重庆市奉节大坪滑坡是由前级浅层的堆积层滑坡和破碎岩石滑坡组合而成的复合型大型老滑坡。根据勘测结果分析,岩层顺倾地区是滑坡易发地区,由于隧道开挖,引起了大坪老滑坡的整体复活。布置测斜孔对滑坡进行深部位移监测,监测结果分析表明:大坪滑坡存在典型滑动带,降雨对滑坡影响较大,滑动面较深,且滑动面以上滑坡体不同部位变形速率不一致,通过明确滑动带的位置、厚度、滑动方向及变形范围,为工程治理设计提供了依据。     

强化质检风险管控 支撑技术服务基础

为贯彻全国铁路工作会议精神,落实铁科院工作会议部署,总结铁道部产品质量监督检验中心2011年工作,分析2012年面临的形势和任务,提出2012年重点工作,以适应新的一年铁路发展对质检工作的新要求、新任务,加快提升质检能力,加强全面风险管理,为铁路发展提供技术基础支持。     

深水浮式生产设施一体化海洋监测系统国产化分析

针对深水浮式生产设施的全方位监测,开展海洋平台监测系统发展和应用现状的国内外调研,阐述一体化海洋监测系统（Integrated Marine Monitoring System,IMMS）关键技术。引入深海一号能源站监测系统实例进行海洋监测系统国产化探索,分析海洋监测系统国产化的发展方向,为今后深水浮式生产设施的安全完整性管理提供借鉴。     

基于物联网的省级交通运输环境监测系统设计——以贵州省为例

从实际项目的需求出发,对基于物联网的省级交通运输环境监测系统进行了架构设计。使用软件工程的分析和设计理念,介绍了贵州省交通运输环境监测系统的需求分析,系统设计过程。为实现贵州省交通运输环境监测网络建设试点工程提供一定的技术支撑。目标是建设一个运行高效的和适应当前交通运输行业发展特点的环境监测系统。     

西部地区公路地质灾害监测预报技术研究

“西部地区公路地质灾害监测预报技术研究”项目针对西部地区公路地质灾害危险性区划、滑坡、崩塌与泥石流监测预报及地质灾害安全管理等关键技术问题进行深入系统研究,形成了公路滑坡、崩塌与泥石流监测预报成套技术,建立了公路地质灾害数据标准,构建了“基于GIS的公路地质灾害监测预报信息系统”平台,实现了公路地质灾害监测实时分析处理和动态预报,为地质灾害综合管理提供技术支撑。     

基于桥梁挠度长期监测值的动态预测

文章针对重庆高家花园嘉陵江大桥实时健康监测系统的挠度长期监测数据,根据监测信息的时间序列呈季节、循环等非平稳状态特点,介绍采用ARMA时间序列预测模型,对挠度监测数据中所包含的外荷载的变化趋势及结构抗力的衰变信息进行动态预测,同时建立了结构外效应的预测函数。结果表明,采用低阶模型能对挠度监测值进行较好的动态预测。     

Strain prediction for critical positions of FPSO under different loading of stored oil using GAIFOA-BP neural network

FPSO (floating, production, storage and offloading) units are widely used in the offshore oil and gas industry. Generally, FPSOs have excellent oil storage capacity owing to their huge oil cargo holds. The volume and distribution of stored oil in the cargo holds influence the strain level of hull girder, especially at critical positions of FPSO. However, strain prediction using structural analysis tools is computationally expensive and time consuming. In this study, a prediction tool based on back-propagation (BP) neural network called GAIFOA-BP is proposed to predict the strain values of concerned positions of an FPSO model under different oil storage conditions. The GAIFOA-BP combines BP model and GAIFOA which is a combination of genetic algorithm (GA) and an improved fruit fly optimization algorithm (IFOA). Results from three benchmark tests show that the GAIFOA-BP model has a remarkable performance. Subsequently, a total of 81 sets of training data and 25 sets of testing data are obtained from experiment using fiber Bragg grating (FBG) sensors installed on the surface of an FPSO model. The numerical results show that the GAIFOA-BP is capable of predicting the strain values with higher accuracy as compared with other BP models. Finally, the reserved GAIFOA-BP model is utilized to predict the strain values under the inputs of a 10-day time series of volume and distribution of stored oil. The predicted strain results are further used to calculate the fatigue consumption of measurement points.     

Experimental field study of floater motion effects on a main bearing in a full-scale spar floating wind turbine

In this paper we present a full-scale experimental field study of the effects of floater motion on a main bearing in a 6 MW turbine on a spar-type floating substructure. Floating wind turbines are necessary to access the full offshore wind power potential, but the characteristics of their operation leave a gap with respect to the rapidly developing empirical knowledge on operation of bottom-fixed turbines. Larger wind turbines are one of the most important contributions to reducing cost of energy, but challenge established drivetrain layouts, component size envelopes and analysis methods. We have used fibre optic strain sensor arrays to measure circumferential strain in the stationary ring in a main bearing. Strain data have been analysed in the time domain and the frequency domain and compared with data on environmental loads, floating turbine motion and turbine operation. The results show that the contribution to fluctuating strain from in-plane bending strain is two orders of magnitude larger than that from membrane strain. The fluctuating in-plane bending strain is the result of cyclic differences between blade bending moments, both in and out of the rotor plane, and is driven by wind loads and turbine rotation. The fluctuating membrane strain appears to be the result of both axial load from thrust, because of the bearing and roller geometry, and radial loads on the rotating bearing ring from total out-of-plane bending moments in the three blades. The membrane strain shows a contribution from slow-varying wind forces and floating turbine pitch motion. However, as the total fluctuating strain is dominated by the intrinsic effects of blade bending moments in these turbines, the relative effect of floater motion is very small. Mostly relevant for the intrinsic membrane strain, sum and difference frequencies appear in the measured responses as the result of nonlinear system behaviour. This is an important result with respect to turbine modelling and simulation, where global structural analyses and local drivetrain analyses are frequently decoupled.