Impact of using text classifiers for standardising maintenance data of wind turbines on reliability calculations
- authored by
- Julia Walgern, Katharina Beckh, Neele Hannes, Martin Horn, Marc Alexander Lutz, Katharina Fischer, Athanasios Kolios
- Abstract
This study delves into the challenge of efficiently digitalising wind turbine maintenance data, traditionally hindered by non-standardised formats necessitating manual, expert intervention. Highlighting the discrepancies in past reliability studies based on different key performance indicators (KPIs), the paper underscores the importance of consistent standards, like RDS-PP, for maintenance data categorisation. Leveraging on established digitalisation workflows, we investigate the efficacy of text classifiers in automating the categorisation process against conventional manual labelling. Results indicate that while classifiers exhibit high performance for specific datasets, their general applicability across diverse wind farms is limited at the present stage. Furthermore, differences in failure rate KPIs derived from manual versus classifier-processed data reveal uncertainties in both methods. The study suggests that enhanced clarity in maintenance reporting and refined designation systems can lead to more accurate KPIs.
- Organisation(s)
-
Institute of Wind Energy Systems
- External Organisation(s)
-
Fraunhofer Institute for Wind Energy Systems (IWES)
University of Strathclyde
Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS)
RWTH Aachen University
Fraunhofer Institute for Energy Economics and Energy System Technology (IEE)
Technical University of Denmark
- Type
- Article
- Journal
- IET renewable power generation
- Volume
- 18
- Pages
- 3463-3479
- No. of pages
- 17
- ISSN
- 1752-1416
- Publication date
- 18.11.2024
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Sustainable Development Goals
- SDG 7 - Affordable and Clean Energy
- Electronic version(s)
-
https://doi.org/10.1049/rpg2.13151 (Access:
Open)
