Artificial Neural Network Based Fault Diagnostic System for Wind Turbines Rüzgar Türbinleri Için Yapay Sinir Aǧi Tabanli Ariza Teşhis Sistemi

Yilmaz O., YÜKSEL T.

30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Turkey, 15 - 18 May 2022, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu55565.2022.9864803
  • City: Safranbolu
  • Country: Turkey
  • Keywords: artificial neural network, fault diagnosis, Wind turbine
  • Bilecik Şeyh Edebali University Affiliated: Yes

Abstract

© 2022 IEEE.Increasing global energy demand and decreasing energy resources have led to an increase in the use of renewable energy resources. In terms of continuity and accessibility of energy, wind energy has the largest share among these resources. The size of the energy demand also increases the turbine dimensions. Due to the growing turbine sizes and increasing electrical power, safety and efficiency factors, the system requires a detection structure against failures. In this study, fault detection was carried out in a three-bladed, horizontal axis, pitch-controlled, 4.8MW turbine. Various data gathered from the system are processed by a decision structure and it makes a decision about the system status. Input data, measured or obtained by various calculations, are used in fault diagnosis with artificial neural network(ANN).