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Wenxian Yang
Wenxian Yang
Professor of Renewable Energy Engineering, The University of Huddersfield
hud.ac.uk의 이메일 확인됨
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Wind turbine condition monitoring: technical and commercial challenges
W Yang, PJ Tavner, CJ Crabtree, Y Feng, Y Qiu
Wind energy 17 (5), 673-693, 2014
5802014
Wind turbine condition monitoring by the approach of SCADA data analysis
W Yang, R Court, J Jiang
Renewable energy 53, 365-376, 2013
4882013
Cost-effective condition monitoring for wind turbines
W Yang, PJ Tavner, CJ Crabtree, M Wilkinson
IEEE Transactions on industrial electronics 57 (1), 263-271, 2009
4812009
Monitoring wind turbine gearboxes
Y Feng, Y Qiu, CJ Crabtree, H Long, PJ Tavner
Wind energy 16 (5), 728-740, 2013
3292013
Machine fault diagnosis through an effective exact wavelet analysis
WT Peter, W Yang, HY Tam
Journal of sound and vibration 277 (4-5), 1005-1024, 2004
3082004
Condition monitoring of the power output of wind turbine generators using wavelets
SJ Watson, BJ Xiang, W Yang, PJ Tavner, CJ Crabtree
IEEE transactions on energy conversion 25 (3), 715-721, 2010
2832010
Condition monitoring and fault diagnosis of a wind turbine synchronous generator drive train
W Yang, PJ Tavner, MR Wilkinson
IET Renewable Power Generation 3 (1), 1-11, 2009
2392009
Optimal design of electric vehicle battery recycling network–From the perspective of electric vehicle manufacturers
L Wang, X Wang, W Yang
Applied Energy 275, 115328, 2020
2242020
Development of an advanced noise reduction method for vibration analysis based on singular value decomposition
WX Yang, WT Peter
Ndt & E International 36 (6), 419-432, 2003
1862003
Interpretation of mechanical signals using an improved Hilbert–Huang transform
WX Yang
Mechanical Systems and Signal Processing 22 (5), 1061-1071, 2008
1052008
Ageing assessment of a wind turbine over time by interpreting wind farm SCADA data
J Dai, W Yang, J Cao, D Liu, X Long
Renewable energy 116, 199-208, 2018
1032018
Superiorities of variational mode decomposition over empirical mode decomposition particularly in time–frequency feature extraction and wind turbine condition monitoring
W Yang, Z Peng, K Wei, P Shi, W Tian
IET Renewable Power Generation 11 (4), 443-452, 2017
1022017
Bivariate empirical mode decomposition and its contribution to wind turbine condition monitoring
W Yang, R Court, PJ Tavner, CJ Crabtree
Journal of Sound and Vibration 330 (15), 3766-3782, 2011
992011
Condition monitoring and damage location of wind turbine blades by frequency response transmissibility analysis
W Yang, Z Lang, W Tian
IEEE Transactions on Industrial Electronics 62 (10), 6558-6564, 2015
922015
Life-cycle assessment of the environmental impact of the batteries used in pure electric passenger cars
X Shu, Y Guo, W Yang, K Wei, G Zhu
Energy Reports 7, 2302-2315, 2021
872021
Wind turbine condition monitoring and fault diagnosis using both mechanical and electrical signatures
W Yang, PJ Tavner, M Wilkinson
2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2008
872008
Detecting impulses in mechanical signals by wavelets
WX Yang, XM Ren
EURASIP Journal on Advances in Signal Processing 2004, 1-7, 2004
872004
Structural health monitoring of composite wind turbine blades: challenges, issues and potential solutions
W Yang, Z Peng, K Wei, W Tian
IET Renewable Power Generation 11 (4), 411-416, 2017
862017
Empirical mode decomposition, an adaptive approach for interpreting shaft vibratory signals of large rotating machinery
W Yang, PJ Tavner
Journal of Sound and Vibration 321 (3-5), 1144-1170, 2009
862009
An online technique for condition monitoring the induction generators used in wind and marine turbines
W Yang, PJ Tavner, R Court
Mechanical Systems and Signal Processing 38 (1), 103-112, 2013
742013
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