Impact of using text classifiers for standardising maintenance data of wind turbines on reliability calculations

verfasst von

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.

Organisationseinheit(en)

Institut für Windenergiesysteme

Externe Organisation(en)

Fraunhofer-Institut für Windenergiesysteme (IWES)
University of Strathclyde
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme (IAIS)
Rheinisch-Westfälische Technische Hochschule Aachen (RWTH)
Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik (IEE)
Technical University of Denmark

Typ

Artikel

Journal

IET renewable power generation

Band

18

Seiten

3463-3479

Anzahl der Seiten

17

ISSN

1752-1416

Publikationsdatum

18.11.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Erneuerbare Energien, Nachhaltigkeit und Umwelt

Ziele für nachhaltige Entwicklung

SDG 7 – Erschwingliche und saubere Energie

Elektronische Version(en)

https://doi.org/10.1049/rpg2.13151 (Zugang: Offen)