Pueltz, Sebastian ; Robin, Yannick ; Koch, Yanik ; Quirnheim Pais, David ; Rauber, Lukas ; Kirchner, Eckhard ; Schuetze, Andreas ; Schneider, Tizian (2022)
Automated condition monitoring for helical gears based on measuring instantaneous angular speed with magnetoresistive sensors.
Sensoren und Messsysteme 2022. Nürnberg (10.05.2022-11.05.2022)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In this work, a novel approach is presented to extract physically motivated features for damage detection of gears in single-stage gearboxes by an automated order analysis of the instantaneous angular speed. This extraction method was applied to measurement data of various magnetoresistive sensors installed in a gearbox test bed and the obtained characteristics were examined in validation scenarios for their susceptibility to external disturbances. The classification results were compared to results obtained with an automatic Machine Learning (ML) method both on the data of the magneto-resistive sensors and an accelerometer. The new method has major advantages, especially with respect to transferability to other rotational speeds.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Pueltz, Sebastian ; Robin, Yannick ; Koch, Yanik ; Quirnheim Pais, David ; Rauber, Lukas ; Kirchner, Eckhard ; Schuetze, Andreas ; Schneider, Tizian |
| Art des Eintrags: | Bibliographie |
| Titel: | Automated condition monitoring for helical gears based on measuring instantaneous angular speed with magnetoresistive sensors |
| Sprache: | Englisch |
| Publikationsjahr: | 11 Mai 2022 |
| Ort: | Berlin |
| Verlag: | VDE-Verlag |
| Buchtitel: | Sensoren und Messsysteme : Beiträge der 21. ITG/GMA-Fachtagung, 10.-11. Mai 2022 in Nürnberg |
| Veranstaltungstitel: | Sensoren und Messsysteme 2022 |
| Veranstaltungsort: | Nürnberg |
| Veranstaltungsdatum: | 10.05.2022-11.05.2022 |
| URL / URN: | https://ieeexplore.ieee.org/document/9861911 |
| Kurzbeschreibung (Abstract): | In this work, a novel approach is presented to extract physically motivated features for damage detection of gears in single-stage gearboxes by an automated order analysis of the instantaneous angular speed. This extraction method was applied to measurement data of various magnetoresistive sensors installed in a gearbox test bed and the obtained characteristics were examined in validation scenarios for their susceptibility to external disturbances. The classification results were compared to results obtained with an automatic Machine Learning (ML) method both on the data of the magneto-resistive sensors and an accelerometer. The new method has major advantages, especially with respect to transferability to other rotational speeds. |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Fachgebiet Produktentwicklung und Maschinenelemente (pmd) |
| Hinterlegungsdatum: | 26 Jul 2023 05:46 |
| Letzte Änderung: | 26 Jul 2023 06:32 |
| PPN: | 509919898 |
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