A big data analysis approach for rail failure risk assessment
Ali Jamshidi,Shahrzad Faghih-Roohi,Siamak Hajizadeh,Alfredo Núñez,Robert Babuska,Rolf Dollevoet,Zili Li,Bart De Schutter +7 more
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This article proposes an image processing approach for automatic detection of squats, especially severe types that are prone to rail breaks, that are detected automatically among the huge number of records from video cameras.Abstract:
Railway infrastructure monitoring is a vital task to ensure rail transportation safety A rail failure could result in not only a considerable impact on train delays and maintenance costs, but also on safety of passengers In this article, the aim is to assess the risk of a rail failure by analyzing a type of rail surface defect called squats that are detected automatically among the huge number of records from video cameras We propose an image processing approach for automatic detection of squats, especially severe types that are prone to rail breaks We measure the visual length of the squats and use them to model the failure risk For the assessment of the rail failure risk, we estimate the probability of rail failure based on the growth of squats Moreover, we perform severity and crack growth analyses to consider the impact of rail traffic loads on defects in three different growth scenarios The failure risk estimations are provided for several samples of squats with different crack growth lengths on a busy rail track of the Dutch railway network The results illustrate the practicality and efficiency of the proposed approachread more
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