| 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 |
Wind power forecasting - A data-driven method along with gated recurrent neural network
Kisvari A, Lin Z, Liu XL
Renewable Energy, 163, 1895, 2021 |
| 3 |
Diagnosis of wind turbine faults with transfer learning algorithms
Chen WQ, Qiu YN, Feng YH, Li Y, Kusiak A
Renewable Energy, 163, 2053, 2021 |
| 4 |
Fault diagnosis of wind turbine with SCADA alarms based multidimensional information processing method
Qiu YN, Feng YH, Infield D
Renewable Energy, 145, 1923, 2020 |
| 5 |
System-wide anomaly detection in wind turbines using deep autoencoders
Renstrom N, Bangalore P, Highcock E
Renewable Energy, 157, 647, 2020 |
| 6 |
Identifying early defects of wind turbine based on SCADA data and dynamical network marker
Fang RM, Wu ML, Guo XH, Shang RY, Shao PF
Renewable Energy, 154, 625, 2020 |
| 7 |
Blades icing identification model of wind turbines based on SCADA data
Dong XH, Gao D, Li J, Zhang JC, Zheng K
Renewable Energy, 162, 575, 2020 |
| 8 |
Investigation of energy output in mountain wind farm using multiple-units SCADA data
Dai JC, Tan YY, Shen XB
Applied Energy, 239, 225, 2019 |
| 9 |
A novel wind turbine condition monitoring method based on cloud computing
Qian P, Zhang DH, Tian XG, Si YL, Li LB
Renewable Energy, 135, 390, 2019 |
| 10 |
Analysis of the efficiency of wind turbine gearboxes using the temperature variable
Sequeira C, Pacheco A, Galego P, Gorbena E
Renewable Energy, 135, 465, 2019 |
