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作 者:封博卿[1] 李平[2] 杨连报[2] FENG Boqing LI Ping YANG Lianbao(China Academy of Railway Sciences, Beijing 100081, China Railway Big Data Research and Application Innovation Center, China Academy of Railway Sciences, Beijing 100081, China)
机构地区:[1]中国铁道科学研究院,北京100081 [2]中国铁道科学研究院铁路大数据研究与应用创新中心,北京100081
出 处:《中国铁路》2017年第1期29-34,共6页China Railway
摘 要:高速铁路基础设施检测领域多年来积累了大量的历史数据,为故障分析及检修决策提供了重要支撑。建立在空间信息技术之上的时空大数据分析为接触网鸟巢病害提供了新的处理和预防方法,能够突破传统分析方法的局限,达到快速、及时的目的,从而有效提高病害处理效率和预防效果,并可降低接触网鸟巢病害处理的成本。基于大数据技术原理,针对接触网鸟害发生时蕴含的时空数据,利用地理信息技术、时空聚合方法等,构建一种基于地理信息的全维度、多层次的鸟巢病害分析流程,补强接触网巡检,为提高接触网鸟巢病害处理能力和预测手段提供新的技术和方法。Over the years, much data have been accumulated in the field of high-speed railway infrastructure, which provide impolxant support tbr fault analysis and decision-making in maintenance. The time-space big data analysis based on spatial intbrmation technology provides a new treatment and prevention method for the harm of bird nests on HSR OCL Capable of what the traditional analysis method cannot achieve, it provides solutions in a rapid and timely manner, so as to effectively improve the efficiency of treatment and prevention of the harm and reduce the cost of its treatment. Based on the principle of big data technology and the space-time data when the harm occurs, this paper develops a full-dimensional and multi-level analysis process of the harm, using geo-information technology and space-time aggregation method, etc., which supplements the patrol inspection of the OCL, and provide a new technology and method to improve the capability of treating and forecasting the harm.
分 类 号:U226.8[交通运输工程—道路与铁道工程] TP391[自动化与计算机技术—计算机应用技术]
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