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  4. Enhancing Wind Farm O&M with SCADA Data-Based Early Fault Detection: Feasibility and Industry Expectations
 
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January 18, 2024
Presentation
Title

Enhancing Wind Farm O&M with SCADA Data-Based Early Fault Detection: Feasibility and Industry Expectations

Title Supplement
Presentation held at EERA DeepWind 2024, January 18, 2024
Author(s)
Lichtenstein, Timo  orcid-logo
Fraunhofer-Institut für Windenergiesysteme IWES  
Maltzahn, Victor von
Fraunhofer-Institut für Windenergiesysteme IWES  
Project(s)
Wind farm virtual Site Assistant for O&M decision support - advanced methods for big data analysis; Teilvorhaben: Methoden und Entscheidungshilfen zur Optimierung von Betrieb und Instandhaltung von Windenergieanlagen  
Funder
Bundesministerium für Wirtschaft und Klimaschutz -BMWK-
Conference
DeepWind - Offshore Wind R&D Conference 2024  
Open Access
File(s)
Download (1.04 MB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.24406/publica-2964
Language
English
Fraunhofer-Institut für Windenergiesysteme IWES  
Keyword(s)
  • Wind turbines

  • Early fault detection

  • SCADA data

  • Operations & Maintenance

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