Optimal track geometry maintenance limits using machine learning: A case study

Kasraei, Ahmad; Zakeri, Jabbar Ali; Bakhtiary, Arash

doi:10.1177/0954409720970096

Cited by 9 publications

(6 citation statements)

References 27 publications

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“…Constructions, operations, designs, and maintenance account to track geometry degradations. Reference [57] assessed PM limits for Iran's railway lines to reduce overall maintenance costs. e study's cost model included PMs, CMs, inspections, and penalties when CMs limits were exceeded.…”

Section: Maintenance Methods Based On Track Geometrymentioning

confidence: 99%

Maintenance Methodologies Embraced for Railroad Systems: A Review

Prabhakaran¹,

Subbaiyan²,

Gopalakrishnan³

et al. 2022

Advances in Materials Science and Engineering

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Congestion on land, hike in fuel costs, and critical need to cut down environmental emissions have generated the urge to shift from conventional rail transit systems to metro rail and high-speed rail for a mass mode of transportation. The conventional railway network especially in India stages an effective space in the means of mass transit systems. Subsequently, periodic inspection of the state of railway tracks is vital for ensuring rail safety, as tracks are critical components of train transportation networks. Tracks are designed to withstand zero critical incidents, and with the advent of new high-speed train services, there is a greater need to focus on track performance. Track maintenance methods are customized to suit local conditions for enhancing safety and reducing disruptions while guaranteeing the resilience and sustainability of any rail system. In recent years, various aspects of the TMSs (track maintenance systems) have been introduced within the railway industry for both ballasted and ballastless track systems. This study reviewed various approaches to track maintenance measures using traditional methods, statistical methods, and geometry-based methods based on track deterioration. Among all the reviewed methods, track maintenance based on the geometry is said to cater to the needs of the maintainers. The outcomes of this study are expected to support and assist in track maintenance decisions in the railway industry.

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Section: Maintenance Methods Based On Track Geometrymentioning

confidence: 99%

Maintenance Methodologies Embraced for Railroad Systems: A Review

Prabhakaran¹,

Subbaiyan²,

Gopalakrishnan³

et al. 2022

Advances in Materials Science and Engineering

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“…The similarity between different categories is as small as possible. 18,19 And the k-means clustering algorithm has an efficient and accurate clustering effect, which are used to process the data of wheel profile. The basic principle is as follows: for a certain data set, k data points can be randomly selected as the clustering center.…”

Section: Principle Of K-means Clustering Algorithmmentioning

confidence: 99%

Optimization of metro wheel reprofiling based on cluster analysis

Lin

Yong

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part F:

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According to the characteristics of the metro vehicles running on the same track leading to a similar wheel wear, a clustering method based on k-means is proposed. The weighted wheel flange height of Sh and qR, and wheel flange thickness of Sd are used as clustering parameters. This paper classifies the treads of the wheels to be repaired and obtains a typical worn wheel profile to reprofile the wheels. Under the premise of ensuring the operation safety of vehicles, the wheel profile optimization model is established for a typical worn wheel profile based on the minimum repair volume. The optimized profile is used as the reprofiling template for all wheels in the same classification. Finally, based on the reprofiling standard for the wheel diameter difference between the left and right wheels, the optimization reprofiling of the wheel profile is achieved. The research results show that the proposed optimization strategy base on cluster analysis can significantly reduce the material removal.

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“…Maintenance planning has always been one of the main issues for railway infrastructure managers ( 3 , 4 ). They seek to adopt a maintenance strategy that provides adequate serviceability and reliability while reducing maintenance costs ( 1, 5–7 ).…”

mentioning

confidence: 99%

“…Meier-Hirmer et al ( 36 ) used a Markov model to calculate maintenance costs. By developing a maintenance model using the standard deviation of the leveling index, Kasraei et al ( 1 ) and Kasraei and Zakeri ( 10 ) examined the effect of different maintenance limits and different inspection intervals on the cost function. In another study, Sancho et al ( 37 ) used the Markov decision process (MDP) approach to determine an optimal strategy with minimum total costs over an infinite horizon.…”

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confidence: 99%

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Maintenance Decision Support Model for Railway Track Geometry Maintenance Planning Using Cost, Reliability, and Availability Factors: A Case Study

Kasraei

Zakeri²

2022

Transportation Research Record: Journal of the Transportation R

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Determining the strategy and planning for maintenance operations on railway tracks is important given the increasing demand from both freight and passengers. An important prerequisite of maintenance planning is the ability to predict the overall and geometric conditions of the railway in the near future. It is, therefore, necessary to develop a degradation model and consider the effect of various maintenance operations using a recovery model. According to EN 13848-5, the alert limit (AL) can be used as an indicator to plan maintenance operations. The current paper benefits from this index as well as the effect of its changes on important parameters such as maintenance costs, availability, and reliability to present a maintenance decision support model. This model allows infrastructure managers to plan maintenance interventions under the conditions of their intended usage strategy. The results of this paper indicate that choosing suitable AL could affect total maintenance cost and availability by up to 57% and 33% respectively.

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Optimal track geometry maintenance limits using machine learning: A case study

Cited by 9 publications

References 27 publications

Maintenance Methodologies Embraced for Railroad Systems: A Review

Maintenance Methodologies Embraced for Railroad Systems: A Review

Optimization of metro wheel reprofiling based on cluster analysis

Maintenance Decision Support Model for Railway Track Geometry Maintenance Planning Using Cost, Reliability, and Availability Factors: A Case Study

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