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Applied Sciences
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Condition Monitoring and Intelligent Maintenance of Railway Infrastructure
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Condition Monitoring and Intelligent Maintenance of Railway Infrastructure

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 8358

Special Issue Editor

Dr. Isidro S. Durazo-Cardenas

E-Mail Website
Guest Editor
School of Aerospace, Transport and Manufacturing, Cranfield University, Bedford MK43 0AL, UK
Interests: autonomous maintenance systems; NDT; data analytics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Condition monitoring and intelligent maintenance systems are crucial to reduce railways’ downtime and increase network availability, enabling new passenger services and reducing operational costs.

In this Special Issue, we invite submissions exploring cutting-edge research and recent advances in the fields of non-destructive testing, condition-based maintenance, prognosis and health management, robotics application, autonomous maintenance systems, track geometry data analyses, and data and visual analytics.

Modeling and experimental studies are welcome, as well as comprehensive review and survey papers.

Dr. Isidro S. Durazo-Cardenas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • non-destructive testing
  • ultrasonics
  • eddy currents
  • condition-based maintenance
  • prognosis
  • health management
  • robotics
  • autonomous maintenance systems
  • track geometry data
  • data analytics
  • visual analytics

Related Special Issue

Published Papers (4 papers)

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Research

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18 pages, 5516 KiB  
Article
Enhancing Railway Network Safety by Reproducing Wheel–Rail Electrical Contact on a Laboratory Scale
by Luna Haydar, Florent Loete, Frédéric Houzé, Tanguy Choupin, Fabien Guiche and Philippe Testé
Appl. Sci. 2023, 13(18), 10253; https://doi.org/10.3390/app131810253 - 13 Sep 2023
Viewed by 984
Abstract
Ensuring the safety of rail networks requires precise detection of a train’s position on a track section. This is achieved using a “track circuit” system, in which the wheel–rail electrical contact is the key to maintaining the system’s reliability. However, any degradation of [...] Read more.
Ensuring the safety of rail networks requires precise detection of a train’s position on a track section. This is achieved using a “track circuit” system, in which the wheel–rail electrical contact is the key to maintaining the system’s reliability. However, any degradation of this contact can lead to a track circuit malfunction known as “deshunting”, creating a serious safety risk for the rail network and for passengers. This paper presents a refined approach to this concern by implementing a laboratory-scale test bench. The main objective is to reproduce the wheel–rail electrical contact under controlled conditions to better understand the various aspects of this contact. The criteria governing the dimensioning of the test bench at reduced scale are based primarily on mechanical considerations. In this study, a series of tests were carried out to investigate the behavior of the electrical resistance as a function of various parameters such as load, current and time. An original homemade salt spray system was designed and used for obtaining controlled rail oxidation. Our preliminary results highlight the impact of these factors on the electrical resistance, providing valuable insights for future advances in rail safety technology. Full article
(This article belongs to the Special Issue Condition Monitoring and Intelligent Maintenance of Railway Infrastructure)
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16 pages, 13020 KiB  
Article
Evaluation of Measurement Strategy for Track Side Monitoring of Railway Wheels
by Matti Rantatalo, Praneeth Chandran, Florian Thiery, Johan Odelius, Christian Gustafsson, Mathias Asplund and Uday Kumar
Appl. Sci. 2023, 13(9), 5382; https://doi.org/10.3390/app13095382 - 25 Apr 2023
Viewed by 1529
Abstract
Wheelsets form an indispensable part of the railway rolling stock and need to be periodically inspected to ensure stable, safe, reliable, and sustainable rail operation. Wheel profiles are usually inspected and measured in a workshop environment using handheld equipment or by utilizing wayside [...] Read more.
Wheelsets form an indispensable part of the railway rolling stock and need to be periodically inspected to ensure stable, safe, reliable, and sustainable rail operation. Wheel profiles are usually inspected and measured in a workshop environment using handheld equipment or by utilizing wayside measuring equipment. A common practice for both methods is to measure the wheel profile at one position along the circumference of the wheel, resulting in a one-slice measurement strategy, based on the assumption that the wheel profile has the same shape independent of the measurement position along the wheel. In this article, the representability of a one-slice measurement strategy with respect to the wheel profile parameters is investigated using handheld measurement equipment. The calculated range of standard deviation of the parameters estimated such as flange height, flange width, flange slope, and hollow wear from the measurements shows a spread in the parameter value along the circumference of the wheel. As an initial validation of the results, measurements from the wayside monitoring systems were also investigated to see if a similar spread was visible. The spread was significantly higher for flange height, flange width, and flange slope estimated from wayside measurement equipment than for the same parameters estimated using the handheld measurement equipment. Full article
(This article belongs to the Special Issue Condition Monitoring and Intelligent Maintenance of Railway Infrastructure)
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23 pages, 4246 KiB  
Article
Metro Track Geometry Defect Identification Model Based on Car-Body Vibration Data and Differentiable Architecture Search
by Zhipeng Wang, Rengkui Liu, Yi Gao and Yuanjie Tang
Appl. Sci. 2023, 13(6), 3457; https://doi.org/10.3390/app13063457 - 8 Mar 2023
Cited by 1 | Viewed by 1800
Abstract
Efficient and low-cost modes for detecting metro track geometry defects (TGDs) are essential for condition-prediction-based preventive maintenance, which can help improve the safety of metro operations and reduce the maintenance cost of metro tracks. Compared with the traditional TGD detection method that utilizes [...] Read more.
Efficient and low-cost modes for detecting metro track geometry defects (TGDs) are essential for condition-prediction-based preventive maintenance, which can help improve the safety of metro operations and reduce the maintenance cost of metro tracks. Compared with the traditional TGD detection method that utilizes the track geometry car, the method that uses a portable detector to acquire the car-body vibration data (CVD) can be used on an ordinary in-service train without occupying the metro schedule line, thereby improving efficiency and reducing the cost. A convolutional neural network-based identification model for TGD, built on a differentiable architecture search, is proposed in this study to employ only the CVD acquired by a portable detector for integrated identification of the type and severity level of TGDs. Second, the random oversampling method is introduced, and a strategy for applying this method is proposed to improve the poor training effect of the model caused by the natural class-imbalance problem arising from the TGD dataset. Subsequently, a comprehensive performance-evaluation metric (track geometry defect F-score) is designed by considering the actual management needs of the metro infrastructure. Finally, a case study is conducted using actual field data collected from Beijing Subway to validate the proposed model. Full article
(This article belongs to the Special Issue Condition Monitoring and Intelligent Maintenance of Railway Infrastructure)
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Review

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30 pages, 17630 KiB  
Review
A Review on the Prospects of Mobile Manipulators for Smart Maintenance of Railway Track
by Miftahur Rahman, Haochen Liu, Isidro Durazo Cardenas, Andrew Starr, Amanda Hall and Robert Anderson
Appl. Sci. 2023, 13(11), 6484; https://doi.org/10.3390/app13116484 - 25 May 2023
Viewed by 3092
Abstract
Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators [...] Read more.
Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research. Full article
(This article belongs to the Special Issue Condition Monitoring and Intelligent Maintenance of Railway Infrastructure)
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