Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review
Yükleniyor...
Dosyalar
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Mdpi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Modern wind turbines operate in continuously transient conditions, with varying speed, torque, and power based on the stochastic nature of the wind resource. This variability affects not only the operational performance of the wind power system, but can also affect its integrity under service conditions. Condition monitoring continues to play an important role in achieving reliable and economic operation of wind turbines. This paper reviews the current advances in wind turbine condition monitoring, ranging from conventional condition monitoring and signal processing tools to machine-learning-based condition monitoring and usage of big data mining for predictive maintenance. A systematic review is presented of signal-based and data-driven modeling methodologies using intelligent and machine learning approaches, with the view to providing a critical evaluation of the recent developments in this area, and their applications in diagnosis, prognosis, health assessment, and predictive maintenance of wind turbines and farms.
Açıklama
Anahtar Kelimeler
wind turbines, condition monitoring, diagnosis, prognosis, machine learning, data mining, health management, operations and maintenance, Bearing Fault-Diagnosis, Deep Learning-Model, Turbine Gearbox, Big-Data, Scada Data, Predictive Maintenance, Acoustic-Emission, Damage Detection, Identification, Performance
Kaynak
Energies
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
14
Sayı
18
