30 citations as recorded by crossref.

1. Physically constrained anomaly repair of wind power time series using TimeGAN Q. Zhang & J. Lv
2. Wind turbine gearbox multi-scale condition monitoring through operational data F. Castellani et al.
3. Wind Turbine SCADA Data Imbalance: A Review of Its Impact on Health Condition Analyses and Mitigation Strategies A. Oliveira-Filho et al.
4. AI-Driven Fault Detection and O&M for Wind Turbine Drivetrains: A Review of SCADA, CMS and Digital Twin Integration N. Jia et al.
5. Early Fault Warning and Identification of Wind Turbines Based on Three-Dimensional Visualization of Dynamic Network Marker Y. Zhou & R. Fang
6. Sensor-error-robust normal-behavior modeling for wind turbine drive train failure prediction using a masked autoencoder X. Chesterman et al.
7. Unsupervised anomaly detection in floating offshore wind turbines based on system responses B. Kang et al.
8. Fault detection in wind turbines using health index monitoring with variational autoencoders S. Wang et al.
9. Scalable SCADA-driven failure prediction for offshore wind turbines using autoencoder-based NBM and fleet-median filtering I. Vervlimmeren et al.
10. Intelligent optimisation for sustainable development of onshore wind farm battery energy storage systems: A systematic review M. Gwabavu et al.
11. A new health indicator for rotating machinery condition monitoring under variable operation conditions through regression among vibration features M. Rao et al.
12. Impact of vibration on wind turbine efficiency and LSTM-based power conversion prediction A. Alutaybi & C. Hamrouni
13. Determining the trend behavior of the wind turbine powertrain using mechanical vibration and seasonal wind data G. Ferri et al.
14. Early fault detection of wind turbine yaw misalignment using Gaussian Mixture Copula Models on SCADA-derived power curves R. Pandit & A. Sreelatha
15. Self-Supervised Condition Monitoring for Wind Turbine Gearboxes Based on Adaptive Feature Selection and Contrastive Residual Graph Neural Network W. Yang et al.
16. Wind energy system fault classification and detection using deep convolutional neural network and particle swarm optimization‐extreme gradient boosting C. Lee & E. Maceren
17. Asset Management decision-making through data-driven Predictive Maintenance – an overview, techniques, benefits and challenges M. Krishna Menon & R. Tuladhar
18. Characterizing the Wake Effects on Wind Power Generator Operation by Data-Driven Techniques D. Astolfi et al.
19. Graph Spatio-Temporal Networks for Condition Monitoring of Wind Turbine X. Jin et al.
20. Use of Artificial Neural Networks and SCADA Data for Early Detection of Wind Turbine Gearbox Failures B. Puruncajas et al.
21. Early detection of gearbox faults in wind turbines using a fine-tuned transformer encoder S. España et al.
22. Floating offshore wind in Japan: addressing the challenges, efforts, and research gaps for large-scale commercialization R. Wada et al.
23. Leveraging signal processing and machine learning for automated fault detection in wind turbine drivetrains F. Jamil et al.
24. Multivariate time-series forecasting of ASTRI-Horn monitoring data: A Normal Behavior Model F. Incardona et al.
25. Simulating run-to-failure SCADA time series to enhance wind turbine fault detection and prognosis A. Eftekhari Milani et al.
26. IoT based monitoring system for DFIG based wind turbines under voltage dips I. Vairavasundaram et al.
27. Recent advances in wind turbine condition monitoring using SCADA data: A state-of-the-art review S. Wang et al.
28. An improved multi-scale convolutional temporal neural network method for wind turbine blade fault diagnosis S. Zhao et al.
29. Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques D. Astolfi et al.
30. A New Two‐Stage Probabilistic Remaining Useful Life Prediction Method for Wind Turbines W. Hu et al.