Prediction Model of Train Fault Probability on Urban Rail Transit Main Line
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1.Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;2.Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety, Tongji University, Shanghai 201804, China;3.Technology Center of Shanghai Shentong Metro Group Co., Ltd., Shanghai 201103, China

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U239.5

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    Abstract:

    A qualitative analysis was made to investigate the major influencing factors in predicting the probability of the train fault happening on urban rail main line. Then, a discrete dataset was collected about a single train’s fault in running for 120 000 km . Three alternative models were established on the basis of the data characteristics, Poisson distribution and zero-inflated Poisson distribution as well as the potential fault forms. According to the comparative study results,a Poisson distribution-based prediction model of train fault probability is finally proposed. Study results show that the train fault probability tends to increase with the increasing of train formation. It decreases first and then increases with the cumulative running kilometers,and the minimum train fault probability occurs in the fourth 120 000 km period, but the initial value is exceeded in the seventh 120 000 km period.

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    Fig.1 Statistics of train fault cause
    Fig.2 Data generation of fault occurrence number for single train in each cumulative running kilometer period
    Fig.3 Trend of train fault frequency with cumulative running kilometer period
    Fig.4 Observation frequencies for different train fault occurrence numbers
    Fig.5 ROC curves for each alternative model
    Table 1
    Table 3
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WANG Zhenbo, YE Xiafei, SHEN Jian, SHI Dongyan. Prediction Model of Train Fault Probability on Urban Rail Transit Main Line[J].同济大学学报(自然科学版),2020,48(12):1751~1757

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  • Received:February 18,2020
  • Online: December 31,2020
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