Jannik Zgraggen

Jannik Zgraggen
ZHAW
School of Engineering
Forschungsschwerpunkt Business Engineering and Operations Management
Technikumstrasse 81
8400 Winterthur
Persönliches Profil
Projekte
- Intelligente Diagnostik von Leistungseinbussen in Solarkraftwerken / Teammitglied / Projekt laufend
- Automatisierte Datenselektion für Anomalieerkennung anhand maschinellen Lernens / Teammitglied / Projekt abgeschlossen
- Convolutional Neural Network Algorithmen für Fehlererkennung bei Windturbinen / Teammitglied / Projekt abgeschlossen
- Machine Learning Based Fault Detection for Wind Turbines / Teammitglied / Projekt abgeschlossen
Publikationen
-
Zgraggen, Jannik; Guo, Yuyan; Notaristefano, Antonio; Goren Huber, Lilach,
2022.
Physics informed deep learning for tracker fault detection in photovoltaic power plants [Paper].
In:
Kulkarni, Chetan; Saxena, Abhinav, Hrsg.,
Proceedings of the Annual Conference of the PHM Society 2022.
14th Annual Conference of the Prognostics and Health Management Society, Nashville, USA, 1-4 November 2022.
PHM Society.
Verfügbar unter: https://doi.org/10.36001/phmconf.2022.v14i1.3235
-
Zgraggen, Jannik; Pizza, Gianmarco; Goren Huber, Lilach,
2022.
Uncertainty informed anomaly scores with deep learning : robust fault detection with limited data [Paper].
In:
Do, Phuc; Michau, Gabriel; Ezhilarasu, Cordelia, Hrsg.,
Proceedings of the 7th European Conference of the Prognostics and Health Management Society 2022.
7th European PHM, Turin, Italy, 6-8 July 2022.
State College:
PHM Society.
S. 530-540.
PHM Society European Conference ; 7.
Verfügbar unter: https://doi.org/10.36001/phme.2022.v7i1.3342
-
Ulmer, Markus; Zgraggen, Jannik; Pizza, Gianmarco; Goren Huber, Lilach,
2022.
Scaling-up deep learning based predictive maintenance for commercial machine fleets : a case study [Paper].
In:
2022 9th Swiss Conference on Data Science (SDS).
9th Swiss Conference on Data Science (SDS), Lucerne, Switzerland, 22-23 June 2022.
IEEE.
S. 40-46.
Verfügbar unter: https://doi.org/10.1109/SDS54800.2022.00014
-
Zgraggen, Jannik; Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,
2021.
Transfer learning approaches for wind turbine fault detection using deep learning [Paper].
In:
Proceedings of the European Conference of the PHM Society 2021.
6th European Conference of the Prognostics and Health Management Society, online, 28 June - 2 July 2021.
PHM Society.
S. 12.
Verfügbar unter: https://doi.org/10.21256/zhaw-22774