Markus Ulmer

Markus Ulmer
ZHAW
School of Engineering
Forschungsschwerpunkt Data Analysis and Statistics
Technikumstrasse 81
8400 Winterthur
Projects
- Data Driven Energy Efficiency / Team member / Project completed
- Convolutional Neural Network Algorithms for Wind Turbine Fault Detection / Team member / Project completed
- Machine Learning Based Fault Detection for Wind Turbines / Team member / Project completed
Publications
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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.
pp. 40-46.
Available from: https://doi.org/10.1109/SDS54800.2022.00014
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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.
pp. 12.
Available from: https://doi.org/10.21256/zhaw-22774
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Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,
2021.
Deep learning for fault detection : the path to predictive maintenance of wind turbines [paper].
In:
Sammelband zu den 6. Energieforschungsgesprächen Disentis.
Energieforschungsgespräche Disentis 2021, online, 20.-22. Januar 2021.
Disentis:
Stiftung Alpines Energieforschungscenter AlpEnForCe.
pp. 24-26.
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Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Goren Huber, Lilach,
2020.
In:
Proceedings of the Annual Conference of the PHM Society 2020.
12th Annual Conference of the PHM Society, virtual, 9-13 November 2020.
PHM Society.
Available from: https://doi.org/10.36001/phmconf.2020.v12i1.1205
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Ulmer, Markus; Jarlskog, Eskil; Pizza, Gianmarco; Manninen, Jaakko; Goren Huber, Lilach,
2020.
Early fault detection based on wind turbine SCADA data using convolutional neural networks [paper].
In:
PHME 2020 : Proceedings of the 5th European Conference of the PHM Society.
5th European Conference of the Prognostics and Health Management Society, Virtual Conference, 27-31 July 2020.
PHM Society.
Available from: https://doi.org/10.36001/phme.2020.v5i1.1217