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eBike measurements for fatigue monitoring and maneuver identification tasks
Metadaten
| Weitere mitwirkende Personen, Institutionen oder Unternehmen | eu - Funder | |
| Weitere mitwirkende Personen, Institutionen oder Unternehmen | Kästner, Markus - ProjectLeader | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Heindel, Leonhard | |
| Kurzbeschreibung | This dataset provides acceleration and strain measurements from a sensor equipped eBike, which were collected for the development of new methods for fatigue damage monitoring and maneuver identification tasks. | |
| Region(en) auf die sich die Daten beziehen | Dresden | |
| Weitere Schlagwörter | Predictive Maintenance | |
| Weitere Schlagwörter | E-Mobility | |
| Weitere Schlagwörter | Fatigue | |
| Weitere Schlagwörter | Damage regression | |
| Sprache | eng | |
| Entstehungsjahr oder Entstehungszeitraum | 2022 | |
| Veröffentlichungsjahr | 2022 | |
| Herausgeber | Technische Universität Dresden | |
| Referenzen auf ergänzende Materialien | IsPartOf: 123456789/5738 (Handle) | |
| Inhalt der Forschungsdaten | Image, Dataset, Software: The dataset mainly includes measurement time series files. Additionally, pictures are included to document the experimental setup and a python script is provided in order to facilitate the data access. | |
| Inhaber der Nutzungsrechte | Technische Universität Dresden | |
| Nutzungsrechte des Datensatzes | CC-BY-4.0 | |
| Eingesetzte Software | Resource Processing: Python | |
| Angabe der Fachgebiete | Engineering | de |
| Titel des Datensatzes | eBike measurements for fatigue monitoring and maneuver identification tasks |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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eBike measurements for fatigue monitoring and maneuver identification tasks [1]
This dataset provides acceleration and strain measurements from a sensor equipped eBike, which were collected for the development of new methods for fatigue damage monitoring and maneuver identification tasks.