| 1 |
Damage detection in operational wind turbine blades using a new approach based on machine learning
Chandrasekhar K, Stevanovic N, Cross EJ, Dervilis N, Worden K
Renewable Energy, 168, 1249, 2021 |
| 2 |
Image recognition of wind turbine blade damage based on a deep learning model with transfer learning and an ensemble learning classifier
Yang XY, Zhang YF, Lv W, Wang D
Renewable Energy, 163, 386, 2021 |
| 3 |
Adaptive fault-tolerant vibration control of a wind turbine blade with actuator stuck
Gao SQ, Liu JK
International Journal of Control, 93(3), 713, 2020 |
| 4 |
An efficient rotational sampling method of wind fields for wind turbine blade fatigue analysis
Chen JB, Song YP, Peng YB, Nielsen SRK, Zhang ZL
Renewable Energy, 146, 2170, 2020 |
| 5 |
Ultrasonic de-icing of wind turbine blades: Performance comparison of perspective transducers
Daniliuk V, Xu YM, Liu RB, He TP, Wang X
Renewable Energy, 145, 2005, 2020 |
| 6 |
A study of dynamic response of a wind turbine blade based on the multi-body dynamics method
Xu J, Zhang L, Li X, Li S, Yang K
Renewable Energy, 155, 358, 2020 |
| 7 |
An effect assessment and prediction method of ultrasonic de-icing for composite wind turbine blades
Wang YB, Xu YM, Lei YY
Renewable Energy, 118, 1015, 2018 |
| 8 |
Mechanical behaviour of thick structural adhesives in wind turbine blades under multi-axial loading
Zarouchas D, Nijssen R
Journal of Adhesion Science and Technology, 30(13), 1413, 2016 |
| 9 |
Composite Repair in Wind Turbine Blades: An Overview
Katnam KB, Comer AJ, Roy D, da Silva LFM, Young TM
Journal of Adhesion, 91(1-2), 113, 2015 |
| 10 |
A dual de-icing system for wind turbine blades combining high-power ultrasonic guided waves and low-frequency forced vibrations
Habibi H, Cheng L, Zheng HT, Kappatos V, Selcuk C, Gan TH
Renewable Energy, 83, 859, 2015 |
