Full Text

Turn on search term navigation

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Real-time and continuous monitoring through smart sensors is considered to be the evolution of traditional track testing, enabling the earlier detection of the main failure modes that degrade railway tracks. Through carrying out preventive maintenance operations, infrastructure resources may be optimized, leading to smarter and more sustainable infrastructure. For this reason, under the larger goal of creating a synergy with various types of sensors for railway tracks, this article presents a critical review on the different, currently available sensors for smart and continuous monitoring. Specifically, the most appropriate monitoring technologies for each of the main railway track failure modes have been assessed and identified, thus deriving the advantages and capacities of each solution. Furthermore, this review presents some of the main experiences carried out to date in literature by using sensor technologies, such as strain gauges, piezoelectric sensors, fiber-optics, geophones and accelerometers. These technologies have proven to offer appropriate characteristics and accuracy for the continuous monitoring of a railway track’s structural state, being capable of measuring different parameters, such as deflections, deformations, stresses or accelerations that would permit the technical tracking of various forms of degradation.

Details

Title
A Critical Review of Sensors for the Continuous Monitoring of Smart and Sustainable Railway Infrastructures
Author
Castillo-Mingorance, Juan Manuel  VIAFID ORCID Logo  ; Moreno-Navarro, Fernando; Rubio-Gámez, María Carmen  VIAFID ORCID Logo 
First page
9428
Publication year
2020
Publication date
2020
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2524902684
Copyright
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.