Special Issue "Monitoring and Maintenance Systems for Railway Infrastructure"
Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 18088
Interests: railway engineering; monitoring of railway infrastructure; modeling of railway infrastructure systems; maintenance strategies for railway systems; transportation networks; model predictive control; computational intelligence; fuzzy systems
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In recent years, various aspects of the railway industry have shown major progress, including the development and application of various new technologies that have facilitated the daily operations of railway systems. Monitoring and maintenance are among the crucial activities that have benefited from these developments. Sensor technologies have allowed the collection of massive amounts of distributed railway infrastructure data. One actual challenge is understanding the relationships between different sources of data and the actual condition of the railway system. Monitoring data are crucial for the design of a maintenance strategy that allows intervention in the infrastructure when, for instance, defects in the catenary or railway track are detected. Maintenance strategies should be tailored to local conditions, minimize the safety and disruption risks, and reduce costs, while ensuring the robustness, sustainability, among other key objectives, for a railway system.
In the railway infrastructure monitoring and maintenance literature, various methods have been proposed. This Special Issue aims to gather contributions oriented toward the design and implementation of both monitoring and maintenance solutions for railway infrastructure systems. We invite contributions on topics related to all aspects of monitoring and maintenance of railway infrastructure, which include, but are not limited to, the following:
- New sensors and measurements for monitoring the health condition of railway systems;
- Detection of defects in railway infrastructure assets such as railway tracks, catenary systems, level crossings, rolling stock, etc.;
- Effective monitoring of railway infrastructure including data-based methods, physical-model-based methods, and hybrid methods;
- Modelling of railway system dynamics and degradation for defining new condition monitoring strategies;
- Novel maintenance strategies including optimization-based approaches, intelligence-based methods, expert systems, and heuristics;
- Design of railway system performance indicators;
- Modelling the impact of disruptions and design and rescheduling of timetables;
- Architecture design for railway big data streaming, processing, and management; and
- Big data approaches to railway infrastructure monitoring and maintenance.
- Artificial Intelligence approaches for railway infrastructure monitoring and maintenance, including various aspects of railway operations.
Dr. Alfredo Núñez
Manuscript Submission Information
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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 2300 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.
- railway engineering
- railway monitoring
- railway maintenance
- railway modelling
- sensors for railway systems