Review and Perspectives of Machine Learning Methods for Wind Turbine Fault Diagnosis
Wind turbines (WTs) generally comprise several complex and interconnected systems, such as hub, converter, gearbox, generator, yaw system, pitch system, hydraulic system control system,integration control system, and auxiliary system. Moreover, fault diagnosis plays an important role in ensuring WT...
Main Authors: | Mingzhu Tang, Qi Zhao, Huawei Wu, Ziming Wang, Caihua Meng, Yifan Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-11-01
|
Series: | Frontiers in Energy Research |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2021.751066/full |
Similar Items
-
Dynamic Condition Adversarial Adaptation for Fault Diagnosis of Wind Turbine Gearbox
by: Hongpeng Zhang, et al.
Published: (2023-11-01) -
Fault Diagnosis Methods Based on Machine Learning and its Applications for Wind Turbines: A Review
by: Tongda Sun, et al.
Published: (2021-01-01) -
Wind Turbine Pitch System Fault Detection Using ssODM-DSTA
by: Mingzhu Tang, et al.
Published: (2021-10-01) -
Research Progress of Video Anomaly Detection Technology
by: WU Kaijun, HUANG Tao, WANG Dicong, BAI Chenshuai, TAO Xiaomiao
Published: (2022-03-01) -
Design and Evaluation of a New Machine Learning Framework for IoT and Embedded Devices
by: Gianluca Cornetta, et al.
Published: (2021-03-01)