期刊文献+

基于轨检大数据的京沪高铁道岔状态评估整治技术及应用

Technology and Application of Turnout Status Evaluation and Treatment Based on Track Inspection Big Data for Beijing-Shanghai HSR
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摘要 京沪高铁共计铺设266组正线道岔,随着服役年限的延长,其结构健康状态逐渐劣化,亟须对其进行系统性评估并开展专项整治,以提高道岔服役状态,保障行车安全平稳。以京沪高铁正线CN道岔为研究对象,提出了基于轨检大数据的京沪高铁道岔状态评估整治技术,利用高速综合检测列车所采集轨道动态检测数据,通过大数据技术对其轨道几何状态进行智能化分析评估。以TQI-T指标为重要参考依据,科学制定道岔整治计划,并融合动、静态轨道几何数据,基于道岔区动、静态2步精调方法对道岔几何线形进行专项整治。通过选取试验区段开展试用及对比分析,试用段内全部正线道岔TQI-T指标均值由4.9 mm降至4.5 mm,其中开展整治作业道岔TQI-T均值由5.2 mm降至4.2 mm。经整治后道岔区列车通过平稳性有效改善,证明所提出方法能够有效改善道岔区几何平顺性并提高列车通过平稳性。 A total of 266 main line turnouts were laid on Beijing-Shanghai HSR.With the extension of service life,the structural health of these turnouts gradually deteriorates,for which systematic evaluation and special treatment are urgently needed to improve the service status of turnouts and ensure safety and stability of train operation.With the CN turnouts on the main line of Beijing-Shanghai HSR as the subject,this paper proposed a technology of status evaluation and treatment for the turnouts based on track inspection big data for Beijing-Shanghai HSR.In accordance with the track dynamic inspection data collected by high speed comprehensive inspection trains,the track geometry was intelligently analyzed and evaluated with the aid of big data technology.With the TQI-T index as an important reference basis,a turnout treatment plan was scientifically formulated,dynamic and static track geometry data were integrated,and the work related to special treatment of the geometric alignment of turnouts was carried out based on the two-step fine adjustment method for the dynamic and static aspects of turnout areas.Test sections were selected for trial and comparative analysis,the average TQI-T index of all the main line turnouts in the trial section was reduced from 4.9 mm to 4.5 mm,and that of turnouts subject to treatment was reduced from 5.2 mm to 4.2 mm.The train passing stability in turnout areas was effectively improved after the treatment,proving that the proposed method can effectively improve the geometric smoothness and train passing stability in turnout areas.
作者 杨怀志 朱星盛 秦航远 孙宪夫 管曙刚 解婉茹 郎海鹏 YANG Huaizhi;ZHU Xingsheng;QIN Hangyuan;SUN Xianfu;GUAN Shugang;XIE Wanru;LANG Haipeng(Beijing-Fuzhou Passenger Dedicated Railway Line Anhui Co.,Ltd.,Hefei Anhui 230031,China;Beijing-Shanghai High Speed Railway Co.,Ltd.,Beijing 100038,China;Infrastructure Inspection Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China;Track Maintenance Department,China Railway Shanghai Group Co.,Ltd.,Shanghai 200071,China;Shanghai High Speed Railway Infrastructure Depot,China Railway Shanghai Group Co.,Ltd.,Shanghai 200439,China)
出处 《中国铁路》 北大核心 2024年第5期1-6,共6页 China Railway
基金 中国铁道科学研究院集团有限公司科研开发基金项目(2022YJ138)。
关键词 京沪高铁 高速道岔 大数据 状态评估 病害整治 轨道质量指数(TQI) Beijing-Shanghai HSR high speed turnout big data status evaluation defect treatment track quality index(TQI)
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