Cargando…
Integral Sensor Fault Detection and Isolation for Railway Traction Drive
Due to the increasing importance of reliability and availability of electric traction drives in Railway applications, early detection of faults has become an important key for Railway traction drive manufacturers. Sensor faults are important sources of failures. Among the different fault diagnosis a...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982243/ https://www.ncbi.nlm.nih.gov/pubmed/29757251 http://dx.doi.org/10.3390/s18051543 |
_version_ | 1783328201162883072 |
---|---|
author | Garramiola, Fernando del Olmo, Jon Poza, Javier Madina, Patxi Almandoz, Gaizka |
author_facet | Garramiola, Fernando del Olmo, Jon Poza, Javier Madina, Patxi Almandoz, Gaizka |
author_sort | Garramiola, Fernando |
collection | PubMed |
description | Due to the increasing importance of reliability and availability of electric traction drives in Railway applications, early detection of faults has become an important key for Railway traction drive manufacturers. Sensor faults are important sources of failures. Among the different fault diagnosis approaches, in this article an integral diagnosis strategy for sensors in traction drives is presented. Such strategy is composed of an observer-based approach for direct current (DC)-link voltage and catenary current sensors, a frequency analysis approach for motor current phase sensors and a hardware redundancy solution for speed sensors. None of them requires any hardware change requirement in the actual traction drive. All the fault detection and isolation approaches have been validated in a Hardware-in-the-loop platform comprising a Real Time Simulator and a commercial Traction Control Unit for a tram. In comparison to safety-critical systems in Aerospace applications, Railway applications do not need instantaneous detection, and the diagnosis is validated in a short time period for reliable decision. Combining the different approaches and existing hardware redundancy, an integral fault diagnosis solution is provided, to detect and isolate faults in all the sensors installed in the traction drive. |
format | Online Article Text |
id | pubmed-5982243 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-59822432018-06-05 Integral Sensor Fault Detection and Isolation for Railway Traction Drive Garramiola, Fernando del Olmo, Jon Poza, Javier Madina, Patxi Almandoz, Gaizka Sensors (Basel) Article Due to the increasing importance of reliability and availability of electric traction drives in Railway applications, early detection of faults has become an important key for Railway traction drive manufacturers. Sensor faults are important sources of failures. Among the different fault diagnosis approaches, in this article an integral diagnosis strategy for sensors in traction drives is presented. Such strategy is composed of an observer-based approach for direct current (DC)-link voltage and catenary current sensors, a frequency analysis approach for motor current phase sensors and a hardware redundancy solution for speed sensors. None of them requires any hardware change requirement in the actual traction drive. All the fault detection and isolation approaches have been validated in a Hardware-in-the-loop platform comprising a Real Time Simulator and a commercial Traction Control Unit for a tram. In comparison to safety-critical systems in Aerospace applications, Railway applications do not need instantaneous detection, and the diagnosis is validated in a short time period for reliable decision. Combining the different approaches and existing hardware redundancy, an integral fault diagnosis solution is provided, to detect and isolate faults in all the sensors installed in the traction drive. MDPI 2018-05-13 /pmc/articles/PMC5982243/ /pubmed/29757251 http://dx.doi.org/10.3390/s18051543 Text en © 2018 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/). |
spellingShingle | Article Garramiola, Fernando del Olmo, Jon Poza, Javier Madina, Patxi Almandoz, Gaizka Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title | Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title_full | Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title_fullStr | Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title_full_unstemmed | Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title_short | Integral Sensor Fault Detection and Isolation for Railway Traction Drive |
title_sort | integral sensor fault detection and isolation for railway traction drive |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982243/ https://www.ncbi.nlm.nih.gov/pubmed/29757251 http://dx.doi.org/10.3390/s18051543 |
work_keys_str_mv | AT garramiolafernando integralsensorfaultdetectionandisolationforrailwaytractiondrive AT delolmojon integralsensorfaultdetectionandisolationforrailwaytractiondrive AT pozajavier integralsensorfaultdetectionandisolationforrailwaytractiondrive AT madinapatxi integralsensorfaultdetectionandisolationforrailwaytractiondrive AT almandozgaizka integralsensorfaultdetectionandisolationforrailwaytractiondrive |