Research on Fault Diagnosis of Wind Turbine Based on SCADA Data
Effective early warning of wind turbine failures is of great significance to reduce the operation and maintenance costs of wind farms and improve power generation efficiency. At present, most wind farms are installed with supervisory control and data acquisition (SCADA) system, and SCADA data contai...
Main Authors: | Yirong Liu, Zidong Wu, Xiaoli Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9216127/ |
Similar Items
-
Fault Diagnosis for Wind Turbines Based on ReliefF and eXtreme Gradient Boosting
by: Zidong Wu, et al.
Published: (2020-05-01) -
Study of Wind Turbine Fault Diagnosis and Early Warning Based on SCADA Data
by: Yilong Shi, et al.
Published: (2021-01-01) -
Development of an SVR Model for the Fault Diagnosis of Large-Scale Doubly-Fed Wind Turbines Using SCADA Data
by: Mingzhu Tang, et al.
Published: (2019-09-01) -
Using eXtreme Gradient BOOSTing to Predict Changes in Tropical Cyclone Intensity over the Western North Pacific
by: Qingwen Jin, et al.
Published: (2019-06-01) -
A New Hybrid Convolutional Neural Network and eXtreme Gradient Boosting Classifier for Recognizing Handwritten Ethiopian Characters
by: Halefom Tekle Weldegebriel, et al.
Published: (2020-01-01)