Subproject: Data-based methods for early fault detection and method transfer to WiSA demonstrator and evaluation

The aim of the "WiSA big data" project is to use the analysis of high-resolution operating data for early fault detection and diagnosis in wind energy power plants support decisions in maintenance planning and implementation.
On the one hand, this is achieved operating data, for application to data with high temporal resolution and on the other hand, novel methods are developed and tested for early fault detection transferred to the wind energy application. The developed and tested methods are subjected to a practice-oriented quantitative comparative evaluation.

Projectduration

01.12.2019 – 30.11.2023

Partners

• Carl-von-Ossietzky Universität Oldenburg
  • Arbeitsgruppe Turbulenz, Windenergie & Stochastik der Universität Oldenburg
  • Arbeitsgruppe Windenergie-Systeme der Universität Oldenburg (ForWind)
  • Institut für Chemie und Biologie des Meeres
• Universität Duisburg-Essen
• Fraunhofer-Institut für Windenergiesysteme IWES
• OFFIS e.V. – Institut für Informatik
• Ramboll GmbH
• Ocean Breeze Energy GmbH & Co. KG
• Deutsche Windtechnik XService GmbH

Associated partners

• Iberdrola Renovables Offshore Deutschland GmbH
• Vattenfall Europe Windkraft GmbH
• ADDITIVE Soft- und Hardware für Technik und Wissenschaft GmbH

Contact persons of VLBA

• Prof. Dr-Ing. Jorge Marx Gómez
• M. Sc. Alexander Atsushi Eguchi
• Dr.-Ing. Andreas Solsbach

Project webpage

www.forwind.de/de/presse/news/20200305-big-data-in-der-windenergie/

Project funding organization

Federal Ministry for Economic Affairs and Energy