A Review of Research on Wind Turbine Bearings’ Failure Analysis and Fault Diagnosis

A Review of Research on Wind Turbine Bearings’ Failure Analysis and Fault Diagnosis

Bearings are crucial components that decide whether or not a wind turbine can work smoothly and that have a significant impact on the transmission efficiency and stability of the entire wind turbine’s life. However, wind power equipment operates in complex environments and under complex working cond...

Full description

Bibliographic Details
Main Authors:	Han Peng, Hai Zhang, Yisa Fan, Linjian Shangguan, Yang Yang
Format:	Article
Language:	English
Published:	MDPI AG 2022-12-01
Series:	Lubricants
Subjects:	wind power bearings bearing failure fault diagnosis technology bearing life
Online Access:	https://www.mdpi.com/2075-4442/11/1/14

Similar Items

Review of Tribological Failure Analysis and Lubrication Technology Research of Wind Power Bearings
by: Han Peng, et al.
Published: (2022-07-01)

Research on Bearing Fault Diagnosis of Wind Turbine Gearbox Based on 1DCNN-PSO-SVM
by: Xiaolin Zhang, et al.
Published: (2020-01-01)

A Probabilistic Bayesian Parallel Deep Learning Framework for Wind Turbine Bearing Fault Diagnosis
by: Liang Meng, et al.
Published: (2022-10-01)

Fault Diagnosis of Wind Turbine Bearings Based on CEEMDAN-GWO-KELM
by: Liping Liu, et al.
Published: (2022-12-01)

HUST bearing: a practical dataset for ball bearing fault diagnosis
by: Nguyen Duc Thuan, et al.
Published: (2023-07-01)

Bearings faults and limits in wind turbine generators
by: Ricardo Manuel Arias Velásquez
Published: (2024-03-01)

Low Latency Bearing Fault Detection of Direct-Drive Wind Turbines Using Stator Current
by: Samrat Nath, et al.
Published: (2020-01-01)

A 2DCNN-RF Model for Offshore Wind Turbine High-Speed Bearing-Fault Diagnosis under Noisy Environment
by: Shujie Yang, et al.
Published: (2022-05-01)

Fault Diagnosis of Rolling Bearing based on MEEMD-DHENN
by: Wang Jinrui, et al.
Published: (2018-01-01)

Rolling Bearing Fault Diagnosis Based on the Coherent Demodulation Model
by: Yinghua Shao, et al.
Published: (2020-01-01)

Method for Evaluating the Reliability and Competitive Failure of Wind Turbine Gearbox Bearings Considering the Fault Incubation Point
by: Weixin Yang, et al.
Published: (2023-07-01)

A fault diagnosis method for rolling bearings of wind turbine generators based on MCGAN data enhancement
by: Zhiyuan Jia, et al.
Published: (2023-09-01)

AN INCIPIENT FAULT DIAGNOSIS METHOD FOR ROLLING BEARING BASED ON MCKD AND LMD
by: SUN Wei, et al.
Published: (2018-01-01)

Increasing Wind Turbine Drivetrain Bearing Vibration Monitoring Detectability Using an Artificial Neural Network Implementation
by: Daniel Strömbergsson, et al.
Published: (2021-04-01)

Scaling Challenges for Conical Plain Bearings as Wind Turbine Main Bearings
by: Jan Euler, et al.
Published: (2023-10-01)

THE EEMD-RA-KU METHOD ON DIAGNOSIS OF BEARING FAULT
by: WU GuangHe, et al.
Published: (2016-01-01)

Research of Fault Diagnosis Method of Rolling Bearing based on Improved CEEMDAN-TKEO
by: Xia Changfeng
Published: (2017-01-01)

An engineering condition indicator for condition monitoring of wind turbine bearings
by: Aijun Hu, et al.
Published: (2020-02-01)

DTM-Bearing: A Novel Framework for Speed-Invariant Bearing Fault Diagnosis Based on Diffusion Transformation Model (DTM)
by: Rijun Liao, et al.
Published: (2024-01-01)

Fuzzy Broad Learning System Combined with Feature-Engineering-Based Fault Diagnosis for Bearings
by: Jianmin Zhou, et al.
Published: (2022-12-01)

Bearing fault diagnosis with parallel CNN and LSTM
by: Guanghua Fu, et al.
Published: (2024-01-01)

Rolling Bearing Diagnosis Based on Composite Multiscale Weighted Permutation Entropy
by: Xiong Gan, et al.
Published: (2018-10-01)

The Partial Reconstruction Symplectic Geometry Mode Decomposition and Its Application in Rolling Bearing Fault Diagnosis
by: Yanfei Liu, et al.
Published: (2023-08-01)

Fault Diagnosis Method for Bearing Based on Attention Mechanism and Multi-Scale Convolutional Neural Network
by: Qimin Shen, et al.
Published: (2024-01-01)

Fault Diagnosis Method for Rolling Bearings Based on Composite Multiscale Fluctuation Dispersion Entropy
by: Xiong Gan, et al.
Published: (2019-03-01)

Fault Diagnosis of Bearings Based on SSWT, Bayes Optimisation and CNN
by: Yan Guohua, et al.
Published: (2023-09-01)

Rolling Bearing Fault Diagnosis Based on WGWOA-VMD-SVM
by: Junbo Zhou, et al.
Published: (2022-08-01)

An Efficient CNN with Tunable Input-Size for Bearing Fault Diagnosis
by: Jungan Chen, et al.
Published: (2021-01-01)

Abnormality Detection Method for Wind Turbine Bearings Based on CNN-LSTM
by: Fanghong Zhang, et al.
Published: (2023-04-01)

Bearing Fault Diagnosis Based on the Switchable Normalization SSGAN with 1-D Representation of Vibration Signals as Input
by: Dongdong Zhao, et al.
Published: (2019-04-01)

Acoustic emission-based early fault detection in tapered roller bearings
by: Hector M. Usgame Sandoval, et al.
Published: (2013-09-01)

Factory-Based Vibration Data for Bearing-Fault Detection
by: Adam Lundström, et al.
Published: (2023-06-01)

FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION
by: WU HaiYan, et al.
Published: (2017-01-01)

Rolling Bearings Fault Diagnosis Method Integrating CEEMDAN-SVD and Cepstrum
by: Jinni ZHENG, et al.
Published: (2021-05-01)

FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM
by: WANG Xia, et al.
Published: (2019-01-01)

Wind Turbine Main Bearing Fault Prognosis Based Solely on SCADA Data
by: Ángel Encalada-Dávila, et al.
Published: (2021-03-01)

CONSIDERATION REGARDING THE DIAGNOSIS AND REPAIR OF BEARINGS
by: Ilie POPP
Published: (2013-05-01)

Bearing Fault Diagnosis based on ACSBP Algorithm
by: Cheng Jiatang, et al.
Published: (2017-01-01)

APPLICATION OF CONVOLUTIONAL NEURAL NETWORK AND CHAOS THEORY IN FAULT DIAGNOSIS OF ROLLING BEARINGS
by: JIN JiangTao, et al.
Published: (2022-01-01)

Research on Bearing Fault Diagnosis Method Based on Filter Features of MOMLMEDA and LSTM
by: Yong Li, et al.
Published: (2019-10-01)