Evaluation and maintenance method for general speed railway turnouts based on multi-source data

被引:0
|
作者
Wang, Pu [1 ]
Yang, Liang [1 ]
Wang, Shuguo [1 ]
Zhang, Huixin [2 ]
Han, Lei [3 ]
Jing, Guoqing [3 ]
机构
[1] China Acad Railway Sci CO Ltd, Railway Engn Res Inst, Beijing, Peoples R China
[2] China Acad Railway Sci, Grad Dept, Beijing, Peoples R China
[3] Beijing Jiaotong Univ, Sch Civil Engn, Beijing, Peoples R China
关键词
Railway turnout maintenance; Turnout service state indicator (TSSI); Analytical target cascading (ATC); Analytic hierarchy process (AHP); Multi-source data analysis;
D O I
10.1016/j.conbuildmat.2024.138896
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In recent years, with the increasing passengers' requirements for safety and comfort, as well as the measures of increasing revenue and reducing the expenditure of railway company, more efficient, more scientific and more comprehensive requirements have been put forward for the maintenance of railway turnouts. This paper develops a maintenance strategy based on the Turnout Service State Indicator (TSSI), derived from an analysis of multi-source data concerning turnout conditions. The weights of critical indicators affecting turnout conditions are determined using Analytical Target Cascading (ATC) and Analytic Hierarchy Process (AHP). Subsequently, turnouts are classified into four categories-great, good, general, and poor-based on their TSSI values, guiding specific maintenance strategies. The proposed assessment method was validated using data from four sets of turnouts collected on actual tracks, showing consistency between the assessment results and field technicians' evaluations. A comparative analysis of the ATC and AHP suggests that the latter provides a more scientific and objective assessment of turnout conditions. The established methods for evaluating the service state and deciding on turnout maintenance actions have been proven feasible and practical through field validation. These methods can be broadly applied to maintain general speed railway turnouts to enhance repair efficiency and reduce maintenance costs.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] A Data-Driven Fault Diagnosis Method for Railway Turnouts
    Ou, Dongxiu
    Xue, Rui
    Cui, Ke
    TRANSPORTATION RESEARCH RECORD, 2019, 2673 (04) : 448 - 457
  • [42] MULTI-SOURCE EVALUATION
    GHOZEIL, S
    JOURNAL OF MEDICAL EDUCATION, 1977, 52 (03): : 230 - 230
  • [43] Traffic Impact Evaluation Method for Urban Large-Scale Activities Based on Multi-Source Data
    Qi, Hao
    Wu, Zhongyi
    Liu, Xianglong
    Weng, Jiancheng
    Qian, Huimin
    CICTP 2020: ADVANCED TRANSPORTATION TECHNOLOGIES AND DEVELOPMENT-ENHANCING CONNECTIONS, 2020, : 254 - 265
  • [44] A Vehicle Speed Prediction Method Integrating Multi-Source Traffic Information Based on Informer
    He, Hongwen
    Xu, Heng
    Li, Menglin
    Niu, Zegong
    2024 12TH INTERNATIONAL CONFERENCE ON TRAFFIC AND LOGISTIC ENGINEERING, ICTLE 2024, 2024, : 72 - 76
  • [45] A New Evaluation Method for Test and Evaluation with Multi-Source Information
    Zhang, Tao
    Sun, Jianbin
    Jiang, Jiang
    Luo, YiYang
    PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, : 3938 - 3943
  • [46] Incremental maintenance of multi-source views
    Moro, G
    Sartori, C
    PROCEEDINGS OF THE 12TH AUSTRALASIAN DATABASE CONFERENCE, ADC 2001, 2001, 23 (02): : 13 - 20
  • [47] A heterogeneous multi-source multi-mode sensory data acquisition method based on data quality
    Ma, Qian
    Gu, Yu
    Zhang, Tian-Cheng
    Yu, Ge
    Gu, Y. (guyu@ise.neu.edu.cn), 1600, Science Press (36): : 2120 - 2131
  • [48] Design and implementation of a fast integration method for multi-source data in high-speed network
    Ma, Lei
    Zhang, Yanning
    Garcia-Diaz, Vicente
    JOURNAL OF HIGH SPEED NETWORKS, 2023, 29 (03) : 251 - 263
  • [49] Separation method for multi-source blended seismic data
    Han-Chuang Wang
    Sheng-Chang Chen
    Bo Zhang
    De-Ping She
    Applied Geophysics, 2013, 10 : 251 - 264
  • [50] Building Contour Optimization Method for Multi-Source Data
    Hu Xiang
    Wu Jianhua
    Wei Ning
    Tu Haowen
    ACTA OPTICA SINICA, 2023, 43 (12)