Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 222222
Loughborough University

Centre for Renewable Energy Systems Technology (CREST)

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Jannis Tautz-Weinert

PhD Research Student

Tel: +44 (0)1509 635305

Location: MBG.0.L01, Garendon Wing

Jannis Weinert is an Early Stage Researcher in the Advanced Wind Energy Systems Operation and Maintenance Expertise (AWESOME) programme, a EC funded Marie Curie Innovative Training Network. His PhD at the Centre of Renewable Energy Systems Technology (CREST), supervised by Professor Simon Watson, focuses on the development of wind turbine fault detection algorithms.

Prior to this position, he finished his wind energy and hydro power specialised MSc in Energy Engineering at the University of Stuttgart, Germany. His master’s thesis at Ramboll Offshore Wind, Hamburg, Germany focused on scour monitoring at offshore wind turbine foundations. Further research included a Student Research Project investigating the acoustic detection of cavitation at hydraulic turbines. He participated in the tidal current turbine development in a six-month internship at Voith Hydro Ocean Current Technologies, Heidenheim, Germany. He obtained a BSc in Renewable Energy Engineering at the University of Stuttgart, too.

Journal Articles

Tautz-Weinert, J and Watson, SJ (2016) Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detectionJournal of Physics: Conference Series, 753(072014), Full text: http://iopscience.iop.org/article/10.1088/1742-6596/753/7/072014. DOI: 10.1088/1742-6596/753/7/072014.

Tautz-Weinert, J and Watson, SJ (2016) Using SCADA Data for Wind Turbine Condition Monitoring - a ReviewIET Renewable Power Generation, ISSN: 1752-1424. Full text: http://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2016.0248. DOI: 10.1049/iet-rpg.2016.0248.



Ibrahim, RK, Tautz-Weinert, J, Watson, SJ (2016) Neural Networks for Wind Turbine Fault Detection via Current Signature Analysis. In WindEurope Summit 2016, Hamburg. Full text: https://windeurope.org/summit2016/conference/proceedings/ .

Weinert, J, Smolka, U, Schümann, B, Chen, PW (2015) Detecting Critical Scour Developments at Monopile Foundations Under Operating Conditions. In European Wind Energy Association Annual Event, EWEA 2015 Scientific Proceedings, Paris, pp.135-139, Full text: http://www.ewea.org/annual2015/wp-content/uploads/files/conference/scientific-proceedings/2015-EWEA-scientific-proceedings.pdf .



Weinert, J and Watson, SJ (2016) Condition monitoring by neural network modelling of drive train temperature, 12th EAWE PhD Seminar on Wind Energy in Europe.

Weinert, J and Watson, SJ (2015) Wind Turbine Fault Detection by Normal Behaviour Modelling, Midlands Energy Consortium Postgraduate Student Conference.