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Angela Meyer

Professor and Research Group Leader

Contact: email_at_angela-meyer.net

Bern University of Applied Sciences

Departm. of Engineering & Information Technology

Quellgasse 21

2501 Biel

Switzerland

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Research

I am a Professor of Applied Machine Learning and Industrial Analytics at the Department of Engineering and Information Technology at Bern University of Applied Sciences. My research aims at developing data-driven and hybrid models and decision support systems to increase the reliability and performance of assets with sensor-driven and machine learning approaches. Today's energy and transport systems are undergoing a lasting structural transformation. Therefore, intelligent operation and maintenance technologies and strategies are becoming increasingly important to enable their reliable, efficient and resilient functioning. Prior to joining academia, I was a doctoral and postdoctoral researcher at ETH Zurich, developed machine learning and predictive maintenance applications at the R&D centre of Hexagon, and led a remote condition monitoring R&D program at Siemens Smart Infrastructure.

News

July 13, 2021: Accepted! Our paper A. Meyer, Multi-target normal behaviour models for wind farm condition monitoring, has been accepted and published in Applied Energy. [Link]

June 10, 2021: Accepted! Our paper A. Meyer, Early fault detection with multi-target neural networks, has been accepted for publication in Lecture Notes in Computer Science and for presentation at ICCSA 2021. [preprint]

June 9, 2021: Our abstract J. Maron, D. Anagnostos, B. Brodbeck, A. Meyer, AI-based condition monitoring and predictive maintenance framework for wind turbines, has been accepted for presentation at WindEurope Electric City in Copenhagen, Denmark in November 2021.

May 19, 2021: We are presenting our work on Multitask learning for data-driven wind farm management and condition-based maintenance at the European Conference on Operational Research in Athens in July 2021 and at the Conference of the International Federation of Operational Research Societies in Seoul in August 2021.

May 7, 2021: We are looking for an early career researcher with strong analytical skills in Predictive Maintenance and Transfer Learning. You will work in an inspiring research environment and collaborate with industry partners. 30 June, 2021: The position is filled now.

May 1, 2021: Our joint research project with a Swiss SME on Predictive Maintenance for Wind Turbines has been approved and is being funded by the Swiss Innovation Agency, Innosuisse. The project aims at developing fault detection algorithms for wind turbine components. We are looking forward to this exciting collaboration!

Apr 17, 2021: Our project proposal Probabilistic Intraday Forecasting of Photovoltaic Power generation for the Swiss Plateau (PIPP) has been approved and is being funded by the Swiss National Science Foundation. The PIPP project aims at developing more accurate forecasting methods of the photovoltaic power generation at lead times of up to several hours. I am hiring a PhD student for this project. We look forward to receiving your online application through our webpage.

Apr. 10, 2021: Our abstract Multitask learning for data-driven wind farm management and condition-based maintenance has been accepted for presentation at the Operations Research 2021 in August 2021.

Feb. 28, 2021: Our paper J. Maron, D. Anagnostos, B. Brodbeck, A. Meyer, Gear bearing fault detection in wind turbines with multi-target neural networks, will be presented at WESC 2021 in May.

Dec. 7, 2020: Submitted our paper A. Meyer, 2020, Multi-target normal behaviour models for wind farm condition monitoring [arXiv]

Nov. 13, 2020: 3nd Smart Maintenance Network online symposium: Antoine Vandyck (Siemens Smart Infrastructures) is presenting Asset Performance Services in Smart Buildings, Data+Service Alliance

Sept. 16, 2020: Speaker of panel discussion on Machine learning and AI in the wind energy industry at the Second Swiss Wind Energy R&D Forum with Dr Sarah Barber (HSR). Registration is open now [Link]

Sept. 9, 2020: Organising a mini-symposium on Data-driven technologies for O&M cost reduction at the Wind Energy Science conference 2021 (WESC 2021) with Dr Ravi Pandit (University of Exeter). Call for abstracts is open! [Link]

Aug. 28, 2020: 2nd Smart Maintenance Network online symposium: Jianwen Meng (Université Paris-Sud) presenting his work on Lithium-ion battery monitoring and fault diagnosis for embedded application, and Florian Pitschi (Swisscom) presenting Condition Monitoring at Meier Tobler – An IoT journey of a Swiss company [Link]

June 15, 2020: Accepted! Our paper: A. Meyer, B. Brodbeck, Data-driven Performance Fault Detection in Commercial Wind Turbines, has been accepted for presentation at the 5th European Conference of the Prognostics and Health Management Society (PHME20).

June 5, 2020: Smart Maintenance Network online symposium, "Fault Detection in CNC machines", Dr Farzam Farbiz (A*STAR Singapore) and "Digital Services and Co-creation in Mobility", Ruben André Lorenzo (Siemens Mobility)  [Link]

May 13, 2020: Accepted! Our paper: L. Vuilleumier, A. Meyer, R. Stöckli, S. Wilbert, L. Zarzalejo, Accuracy of satellite-derived Solar Direct Irradiance in Southern Spain and Switzerland, has been accepted for publication in the International Journal of Remote Sensing [Download]

May 5, 2020: Presented our work on performance-related fault detection in wind turbines at the Prognostics and Health Management conference PHM2020, Besancon.

Apr. 30, 2020: Submitted our paper A. Meyer, B. Brodbeck, 2020, Performance Fault Detection in Wind Turbines by Dynamic Reference State Estimation [arXiv]

Mar. 28, 2020: Filed a patent application on performance optimization methods for renewable power plants with WinJi AG.

Feb. 5, 2020: Presented our work on fault detection and diagnosis in wind turbines at the Swissmem conference Industrie 2025 at ETH Zurich. 

Jan. 21, 2020: Swiss Smart Maintenance network chair, "Condition-based maintenance and resistance to change", USU AG/Heidelberger Druckmaschinen  [Link]

Nov. 19, 2019: Swiss Smart Maintenance network chair, "Deep-learning for Tunnel inspections", LeanBI/Amberg Technologies, Data+Service Alliance [Link]

Peer-reviewed Publications

  • Meyer, A. (2021): Multi-target normal behaviour models for wind farm condition monitoring, Applied Energy, Elsevier, doi: 10.1016/j.apenergy.2021.117342. [Link]

  • Meyer, A. (2021): Early fault detection with multi-target neural networks, Lecture Notes in Computer Science, Springer, accepted.

  • Meyer, A., B. Brodbeck (2020): Data-driven Performance Fault Detection in Commercial Wind Turbines, Proceedings of the 5th European Conference of the Prognostics and Health Management Society (PHME20), ISBN 978-1-93-626332-5, Download.

  • Vuilleumier, L.*, A. Meyer*, R. Stöckli, S. Wilbert, L. Zarzalejo (2020): Accuracy of Satellite-derived Solar Direct Irradiance in Southern Spain and Switzerland, International Journal of Remote Sensing, doi: 10.1080/01431161.2020.1783712. *shared first authorship

  • Kuhn, P., S. Wilbert, C. Prahl, D. Garsche, D. Schüler, T. Haase, L. Ramirez, L. Zarzalejo, A. Meyer, P. Blanc, R. Pitz-Paal (2018): Applications of a shadow camera system for energy meteorology, Advances in Science and Research, doi: 10.5194/asr-15-11-2018.

  • Kuhn, P., S. Wilbert, C. Prahl, D. Schüler, T. Haase, T. Hirsch, M. Wittmann, L. Ramirez, L. Zarzalejo, A. Meyer, L. Vuilleumier, P. Blanc, R. Pitz-Paal (2017): Shadow camera system for the generation of solar irradiance maps, Solar Energy, doi: 10.1016/j.solener.2017.05.074.

  • Gasparini, B.*, A. Meyer*, D. Neubauer, S. Münch, U. Lohmann (2017): Cirrus cloud properties as seen by the CALIPSO satellite and ECHAM-HAM global climate model, Journal of Climate, doi: 10.1175/JCLI-D-16-0608.1. *shared first authorship

  • Kuhn, P., B. Nouri, S. Wilbert, C. Prahl, N. Kozonek, T. Schmidt, Z. Yasser, L. Ramirez, L. Zarzalejo, , L. Vuilleumier, D. Heinemann, P. Blanc, R. Pitz‐Paal (2017): Validation of an all‐sky imager–based nowcasting system for industrial PV plants, Progress in Photovoltaics: Research and Applications, 26, doi: 10.1002/pip.2968.

  • Meyer, A., L. Vuilleumier, R. Stöckli, S. Wilbert, L. Zarzalejo (2017): Validation of Direct Normal Irradiance from Meteosat Second Generation, Conference Paper presented at European Meteorological Society Annual Meeting 2017, EMS2017-365-1.

  • Kuhn, P., S. Wilbert, D. Schüler, C. Prahl, T. Haase, L. Ramirez, L. Zarzalejo, A. Meyer, L. Vuilleumier, P. Blanc, J. Dubrana, A. Kazantzidis, M. Schroedter-Homscheidt, T. Hirsch, R. Pitz-Paal (2017): Validation of spatially resolved all sky imager derived DNI nowcasts, AIP Conference Proceedings, doi: 10.1063/1.4984522.

  • Meyer, A., L. Vuilleumier, R. Stöckli, S. Wilbert, L. Zarzalejo (2016): Validation of Direct Normal Irradiance from Meteosat Second Generation, Conference Paper presented at European Geosciences Union General Assembly 2016, EPSC2016-14541.

  • Meyer, A., D. Folini, U. Lohmann, and T. Peter (2016): Tropical temperature and precipitation responses to large volcanic eruptions: Observations and AMIP5 simulations, Journal of Climate, doi: 10.1175/JCLI-D-15-0034.1.

  • Meyer, A., J.-P. Vernier, B. Luo, U. Lohmann, and T. Peter (2015): Did the 2011 Nabro eruption affect the optical properties of ice clouds?, J. Geophys. Res. Atmos., 120, doi: 10.1002/2015JD023326.