Dr. Jan Thomas Palmé
Dr. Jan Thomas Palmé
ZHAW
School of Engineering
Technikumstrasse 81
8400 Winterthur
Work at ZHAW
Position
Senior Lecturer
Professional development teaching
Experience
- Senior Analytics Engineer
General Electric Gas Power
08 / 2016 - 08 / 2021 - Team Leader Condition Assessment & Monitoring
Alstom Power, Thermal Service
08 / 2013 - 07 / 2016 - R&D Engineer
Alstom Power, Thermal Service
06 / 2011 - 07 / 2013
Projects
- Condition Monitoring of Generators / Project leader / laufend
- Defect detection of production devices / Project leader / abgeschlossen
- End-to-End Data Driven Design of After-Sales-Services for Digital Cutters / Team member / abgeschlossen
- Expert Group Smart Maintenance / Deputy project leader / abgeschlossen
Publications
-
Goren Huber, Lilach; Palmé, Thomas; Arias Chao, Manuel,
2023.
Physics-informed machine learning for predictive maintenance : applied use-cases [paper].
In:
2023 10th IEEE Swiss Conference on Data Science (SDS).
10th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 22-23 June 2023.
IEEE.
pp. 66-72.
Available from: https://doi.org/10.1109/SDS57534.2023.00016
-
Goren Huber, Lilach; Palmé, Jan Thomas; Arias Chao, Manuel,
2023.
Hybride Instandhaltung : wie fliesst das Fachwissen in die KI?.
fmpro service.
2023(6), pp. 5-7.
Available from: https://doi.org/10.21256/zhaw-29515
Publications before appointment at the ZHAW
- Magnus Fast, Thomas Palmé, Magnus Genrup, "A Novel Approach for Gas Turbine Condition Monitoring Combining CUSUM Technique and Artificial Neural Network", 2009, ASME Turbo Expo 2009: Power for Land, Sea, and Air, June 8–12, 2009, Orlando, Florida, USA
- Thomas Palmé, Magnus Fast, Mohsen Assadi, Andrew Pike, Peter Breuhaus "Different Condition Monitoring Models for Gas Turbines by Means of Artificial Neural Networks", ASME Turbo Expo 2009: Power for Land, Sea, and Air June 8–12, 2009 Orlando, Florida, USA
- M. Fast, Thomas Palmé, "Application of artificial neural networks to the condition monitoring and diagnosis of a combined heat and power plant" Energy, Volume 35, Issue 2, February 2010, Pages 1114-1120
- Thomas Palmé, Peter Breuhaus, Mohsen Assadi, Albert Klein, Minkyo Kim, "Early Warning of Gas Turbine Failure by Nonlinear Feature Extraction Using an Auto-Associative Neural Network Approach" ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition June 6–10, 2011, Vancouver, British Columbia, Canada
- Thomas Palmé, Peter Breuhaus, Mohsen Assadi, Albert Klein, Minkyo Kim "New Alstom Monitoring Tools Leveraging Artificial Neural Network Technologies" ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition June 6–10, 2011 Vancouver, British Columbia, Canada
- Thomas Palmé, Magnus Fast, Marcus Thern "Gas turbine sensor validation through classification with artificial neural networks" November 2011Applied Energy 88(11):3898-3904
- Thomas Palmé, Francois Liard, Dirk Therkorn "Similarity Based Modeling for Turbine Exit Temperature Spread Monitoring on Gas Turbines" ASME Turbo Expo 2013: Turbine Technical Conference and Exposition, June 3–7, 2013 San Antonio, Texas, USA
- Brien Jeffries, J. Wesley Hines, Albert Klein, Thomas Palmé, Romain Bayère "Early Detection of Boiler Leakage in a Combined Cycle Power Plant Using an Auto Associative Kernel Regression Model" ASME Turbo Expo 2013: Turbine Technical Conference and Exposition, June 3–7, 2013 San Antonio, Texas, USA
- Thomas Palmé, Francois Liard, Dan Cameron "Hybrid Modeling of Heavy Duty Gas Turbines for On-Line Performance Monitoring" ASME Turbo Expo 2014: Turbine Technical Conference and Exposition June 16–20, 2014, Düsseldorf, Germany
- Martin Gassner, John Nilsson, Emma Nilsson, Thomas Palmé, Heiko Züfle, Stefano Bernero "A Data-Driven Approach for Analysing the Operational Behaviour and Performance of an Industrial Flue Gas Desulphurisation Process" Computer Aided Chemical Engineering Volume 33, 2014, Pages 661-666
- Yang Hu, Olga Fink, Thomas Palmé "Online sequential extreme learning machines for fault detection" 2016 IEEE International Conference on Prognostics and Health Management (ICPHM)
- Hu, Y., Palmé, T., & Fink, O. (2016). Deep Health Indicator Extraction: A Method based on Auto-encoders and Extreme Learning Machines. Annual Conference of the PHM Society, 8(1). https://doi.org/10.36001/phmconf.2016.v8i1.2587
- Yang Hu, Thomas Palmé, Olga Fink, "Fault detection based on signal reconstruction with Auto-Associative Extreme Learning Machines", Engineering Applications of Artificial Intelligence, Volume 57, 2017,Pages 105-117, ISSN 0952-1976
- Michau, G., Palm´, T., & Fink, O. (2017). Deep Feature Learning Network for Fault Detection and Isolation. Annual Conference of the PHM Society, 9(1). https://doi.org/10.36001/phmconf.2017.v9i1.2380
- Gabriel Michau, Olga Fink, Thomas Palmé "Fleet PHM for Critical Systems: Bi-level Deep Learning Approach for Fault Detection" Conference: Proceedings of the European Conference of the PHM Society 2018At: Utrecht, Netherlands
- Michau G, Hu Y, Palmé T, Fink O. Feature learning for fault detection in high-dimensional condition monitoring signals. Proceedings of the Institution of Mechanical Engineers, Part O. 2019;234(1):104-115.
- Thomas Palmé, Phillip Waniczek, Herwart Hönen, Mohsen Assadi, Peter Jeschke "Compressor Map Prediction by Neural Networks", Journal of Energy and Power Engineering 6 (2012) 1651-1662