Jannik Zgraggen

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

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