Full metadata record
DC FieldValueLanguage
dc.contributor.authorClimaco, Paolo-
dc.contributor.authorGarcke, Jochen-
dc.contributor.authorIza Teran, Victor Rodrigo-
dc.contributor.authorLecei, Ivan-
dc.date.accessioned2022-10-26T06:27:30Z-
dc.date.available2022-03-31T03:46:51Z-
dc.date.available2022-10-26T06:27:30Z-
dc.date.issued2022-
dc.identifier.urihttps://fordatis.fraunhofer.de/handle/fordatis/262.3-
dc.identifier.urihttp://dx.doi.org/10.24406/fordatis/191.3-
dc.description.abstractThis dataset consists of simulated acceleration signals representing the vibration response of a generic geared-rotor bearing system made of a rigid gearbox with a spur gear pair mounted on flexible shafts supported by rolling element bearings. The signals include a stochastic component simulating the varying load condition caused by wind turbulence. The data have been generated simulating two distinct gearbox health scenarios and two wind speed conditions. Specifically, signals represent a situation in which a perfectly healthy gearbox is modelled or a scenario in which one of the gears is damaged. The simulated damage consists of a cracked tooth in one of the two gears. Moreover, independently of the gearbox's health condition, we consider the two wind speed scenarios of 5 m/s and 13m/s. Further information on the data can be found in the 'Readme.md' file.en
dc.description.sponsorshipThe dataset has been created as part of the project MADESI, which has been granted by the BMBF within their announcement “Richtlinie zur Förderung von Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens.”en
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/en
dc.subjectwind turbine gearboxen
dc.subject.ddcDDC::500 Naturwissenschaften und Mathematiken
dc.titleWind turbine gearbox simulation dataen
dc.typeTabular Dataen
dc.contributor.funderBundesministerium für Bildung und Forschung BMBF (Deutschland)en
dc.description.technicalinformationThis dataset has been described and analyzed in the paper ["Multi-resolution Dynamic Mode Decomposition for Damage Detection in Wind Turbine Gearboxes"](https://arxiv.org/abs/2110.04103) accepted for publication at [Data-Centric Engineering](https://www.cambridge.org/core/journals/data-centric-engineering). The workflow on generating the simulated signals can be found at [github.com/Fraunhofer-SCAI/mrDMD-damage-detection](https://github.com/Fraunhofer-SCAI/mrDMD-damage-detection).en
fordatis.instituteSCAI Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnenen
fordatis.rawdatatrueen
fordatis.sponsorship.projectid01IS18043Aen
fordatis.sponsorship.projectnameMaschine Lernverfahren für Stochastisch-Deterministische Multi-Sensor Signaleen
fordatis.sponsorship.projectacronymMADESIen
fordatis.date.start2020-
fordatis.date.end2021-
Appears in Collections:Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI


Version History
Version Item Date Summary
3 fordatis/262.3 2022-10-24 12:17:26.909 Reviewer des assoziierten Papers möchte gerne mehr Variation in den Daten haben
1 fordatis/262 2022-03-31 05:46:51.0

This item is licensed under a Creative Commons License Creative Commons