Review of high-speed train maintenance

Fu, Zhenliang; Wang, Guiguo; Gao, Feng; Tian, Xueyan; Li, Yonghua; Bi-hong, LU

doi:10.1109/icqr2mse.2012.6246266

Cited by 8 publications

(2 citation statements)

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“…These approaches can vary between countries as can be seen throughout Japan, Germany and France and their high speed railway systems, with different granularity or degrees of maintenance split among a number of levels. These levels cover simpler and more routine maintenance such as inspection and cleaning needed after daily operation to much more complex and intensive overhaul and repair (body update, paint, seat replacement) [8]. The integration of some form of automation into either of these maintenance levels may be a driver for further reduction in costs and also lead to improved through life performance of the asset.…”

Section: Maintenance Repair and Overhaulmentioning

confidence: 99%

Autonomous Maintenance for Through-Life Engineering

Farnsworth

Bell

Khan

et al. 2014

Decision Engineering

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This chapter looks at the overall theme of automating maintenance practices with a particular focus upon the application of robotics within this field. Covering the current state of the art in automating maintenance processes this chapter also looks at the current challenges to moving beyond simple inspection and diagnosis to the design and construction of fully automated platforms for undertaking maintenance. This includes methodologies for capturing and classifying maintenance task processes so that they can be automated in some way and how to link this task classification with some level of automation. The chapter ends with a discussion on how the design process can be adapted to aid automated maintenance, self-healing and no fault found applications.

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Section: Maintenance Repair and Overhaulmentioning

confidence: 99%

Autonomous Maintenance for Through-Life Engineering

Farnsworth

Bell

Khan

et al. 2014

Decision Engineering

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“…Added to this it must be remembered drift probability [20]. The theories and the definition about the best inspection process are really complex, for instance in the machines which are working all time it is necessary to develop maintenance methodologies to avoid the failure or breakdown maintenance, in this sense, preventive maintenance and reliability-centered maintenance, among others need to be included [21]. This chapter includes a description of a methodology for damage detection and classification and the experimental validation with data from an aluminum plate instrumented with piezoelectric transducers permanently attached to its surface.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Methodologies for Structural Damage Detection Based on Machine Learning Applications

Vitola¹,

Anaya²,

Burgos³

et al. 2016

Pattern Recognition - Analysis and Applications

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Structural health monitoring (SHM) is an important research area, which interest is the damage identification process. Different information about the state of the structure can be obtained in the process, among them, detection, localization and classification of damages are mainly studied in order to avoid unnecessary maintenance procedures in civilian and military structures in several applications. To carry out SHM in practice, two different approaches are used, the first is based on modelling which requires to build a very detailed model of the structure, while the second is by means of data-driven approaches which use information collected from the structure under different structural states and perform an analysis by means of data analysis. For the latter, statistical analysis and pattern recognition have demonstrated its effectiveness in the damage identification process because real information is obtained from the structure through sensors installed permanently to the observed object allowing a real-time monitoring. This chapter describes a damage detection and classification methodology, which makes use of a piezoelectric active system which works in several actuation phases and that is attached to the structure under evaluation, principal component analysis, and machine learning algorithms working as a pattern recognition methodology. In the chapter, the description of the developed approach and the results when it is tested in one aluminum plate are also included.

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Intelligent Technologies in High-Speed Rail Transit Systems

Prasad,

Jain

2024

Energy, Environment, and Sustainability

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Review of high-speed train maintenance

Cited by 8 publications

References 0 publications

Autonomous Maintenance for Through-Life Engineering

Autonomous Maintenance for Through-Life Engineering

Data-Driven Methodologies for Structural Damage Detection Based on Machine Learning Applications

Intelligent Technologies in High-Speed Rail Transit Systems

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