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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Climaco, Paolo | - |
dc.contributor.author | Garcke, Jochen | - |
dc.contributor.author | Iza Teran, Victor Rodrigo | - |
dc.contributor.author | Lecei, Ivan | - |
dc.date.accessioned | 2022-03-31T03:46:51Z | - |
dc.date.available | 2022-03-31T03:46:51Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://fordatis.fraunhofer.de/handle/fordatis/262 | - |
dc.identifier.uri | http://dx.doi.org/10.24406/fordatis/191 | - |
dc.description.abstract | Files containing acceleration signals, representing the vibration response of the modelled gearbox for three full rotations of the shaft. S={5,13} indicates the wind (W) speed considered in the simulation, while X={h,cr} indicates the health condition. 'cr' indicates that the simulation includes the cracked tooth. On the contrary, 'h' indicates that the signal has been produced considering a healthy gearbox and not including damage. Y= {1,2,3} indicates the set of excitation parameters chosen to simulate the signal. The three different excitation parameters (ep) settings used for the experiments can be consulted in Table 4 of the paper. Z={10,13,16} relates to the different crack lengths simulated. Specifically, it indicates the percentage of the dimensionless stiffness function's decrease applied to simulate the tooth crack (tc). | en |
dc.description.sponsorship | The 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.iso | en | en |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-sa/4.0/ | en |
dc.subject | WindTurbine Gearbox | en |
dc.subject.ddc | DDC::500 Naturwissenschaften und Mathematik | en |
dc.title | Wind turbine gearbox simulation data | en |
dc.type | Tabular Data | en |
dc.contributor.funder | Bundesministerium für Bildung und Forschung BMBF (Deutschland) | en |
dc.description.technicalinformation | The data is created using matlab. The data is is saved in the mat-format. | en |
fordatis.institute | SCAI Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen | en |
fordatis.rawdata | true | en |
fordatis.sponsorship.projectid | 01IS18043A | en |
fordatis.sponsorship.projectname | Maschine Lernverfahren für Stochastisch-Deterministische Multi-Sensor Signale | en |
fordatis.sponsorship.projectacronym | MADESI | en |
fordatis.date.start | 2020 | - |
fordatis.date.end | 2021 | - |
Enthalten in den Sammlungen: | Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI |
Dateien zu dieser Ressource:
Versionshistorie
Version | Ressource | Datum | Zusammenfassung |
---|---|---|---|
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 |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons