dc.rights.license | Attribution 4.0 International | * |
dc.contributor.author | Garramiola, Fernando | |
dc.contributor.author | del-Olmo, Jon | |
dc.contributor.author | Madina, Patxi | |
dc.contributor.author | Almandoz, Gaizka | |
dc.contributor.author | Poza, Javier | |
dc.date.accessioned | 2018-10-24T12:36:17Z | |
dc.date.available | 2018-10-24T12:36:17Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 1424-8220 | eu_ES |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=147662 | eu_ES |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/1104 | |
dc.description.abstract | 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. | eu_ES |
dc.description.sponsorship | This research work was supported by CAF Power & Automation. The authors are thankful to the colleagues from CAF Power & Automation, who provided material and expertise that greatly assisted the research. | eu_ES |
dc.language.iso | eng | eu_ES |
dc.publisher | MDPI AG | eu_ES |
dc.rights | © 2018 by the authors | eu_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | sensor fault diagnosis | eu_ES |
dc.subject | diagnostic observer | eu_ES |
dc.subject | fault injection | eu_ES |
dc.subject | railway traction drive | eu_ES |
dc.subject | frequency analysis | eu_ES |
dc.title | Integral Sensor Fault Detection and Isolation for Railway Traction Drive | eu_ES |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | eu_ES |
dcterms.source | Sensors | eu_ES |
local.contributor.group | Accionamientos aplicados a la tracción y a la generación de energía eléctrica | eu_ES |
local.description.peerreviewed | true | eu_ES |
local.identifier.doi | http://dx.doi.org/10.3390/s18051543 | eu_ES |
local.source.details | Vol. 18. Nº 5. 1543. Special Issue: Sensors for Fault Detection), 2018 | eu_ES |
oaire.format.mimetype | application/pdf | |
oaire.file | $DSPACE\assetstore | |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | eu_ES |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | eu_ES |