P. Tavner, Offshore Wind Turbines-Reliability, availability and maintenance. The Institution of Engineering and Technology, 2012.
DOI : 10.1049/pbrn013e

R. Iserman, Fault Diagnosis Systems-An Introduction from Fault Detection to Fault Tolerance, 2006.

P. Tchakoua, R. Wamkeue, M. Ouhrouche, F. Slaoui-hasnaoui, T. A. Tameghe et al., Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges. Energies, vol.7, 2014.

W. Qiao and D. Lu, A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis-Part I: Components and Subsystems, IEEE Transactions on Industrial Electronics, vol.62, issue.10, pp.6536-6545, 2015.

W. Qiao and D. Lu, A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis-Part II: Signals and Signal Processing Methods, IEEE Transactions on Industrial Electronics, vol.62, issue.10, pp.6546-6557, 2015.

W. Yang, P. J. Tavner, C. J. Crabtree, Y. Feng, and Y. Qiu, Wind turbine condition monitoring: technical and commercial challenges, Wind Energy, vol.17, issue.5, pp.673-693, 2014.

D. Mcmillan and G. W. Ault, Quantification of condition monitoring benefit for offshore wind turbines, Wind Engineering, vol.31, issue.4, pp.267-285, 2007.

W. Yang, R. Court, and J. Jiang, Wind turbine condition monitoring by the approach of SCADA data analysis, vol.53, pp.365-376, 2013.

A. Lebranchu, S. Charbonnier, C. Bérenguer, and F. Prevost, Review and analysis of SCADA data-based methods for health monitoring of wind turbines, Safety and Reliability of Complex Engineered Systems-Proc. of the 25th European Safety and Reliability Conference (ESREL 2015), pp.2413-2421, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01237912

D. Mclaughlin, P. J. Clive, and J. H. Mckenzie, Wind farm performance assessment in the real world, Proceedings of the 2009 European Wind Energy Conference & Exhibition, pp.4520-4528, 2009.

P. Cambron, R. Lepvrier, C. Masson, A. Tahan, and F. Pelletier, Power curve monitoring using weighted moving average control charts, vol.94, pp.126-135, 2016.

S. Butler, J. Ringwood, and F. O'connor, Exploiting SCADA system data for wind turbine performance monitoring, 2013 Conference on Control and Fault-Tolerant Systems (SysTol), pp.389-394, 2013.

F. Elijorde, S. Kim, and J. Lee, A Wind Turbine Fault Detection Approach Based on Cluster Analysis and Frequent Pattern Mining, KSII Transactions on Internet and Information Systems, vol.8, issue.2, pp.664-677, 2014.

S. Li, D. C. Wunsch, E. A. O'hair, and M. G. Giesselmann, Using neural networks to estimate wind turbine power generation, IEEE Transactions on Energy Conversion, vol.16, issue.3, pp.276-282, 2001.

M. Schlechtingen, I. F. Santos, and S. Achiche, Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 1: System description, Applied Soft Computing, vol.13, issue.1, pp.259-270, 2013.

M. Schlechtingen and I. F. Santos, Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 2: Application examples, Applied Soft Computing, vol.14, pp.447-460, 2014.

M. Wilkinson, K. Harman, T. Van-delft, and B. Darnell, Comparison of methods for wind turbine condition monitoring with SCADA data, IET Renewable Power Generation, vol.8, issue.4, pp.390-397, 2014.

M. Schlechtingen and I. F. Santos, Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection. Mechanical Systems and Signal Processing, vol.25, pp.1849-1875, 2011.

W. G. Garlick, R. Dixon, and S. J. Watson, A model-based approach to wind turbine condition monitoring using SCADA data, 0th Int. Conf. System Engineering, 2009.

P. Cross and X. Ma, Model-based and fuzzy logic approaches to condition monitoring of operational wind turbines, International Journal of Automation and Computing, vol.12, issue.1, pp.25-34, 2015.

M. C. Garcia, M. A. Sanz-bobi, and J. Del-pico, SIMAP: Intelligent System for Predictive Maintenance: Application to the health condition monitoring of a windturbine gearbox, Computers in Industry, vol.57, issue.6, pp.552-568, 2006.

A. S. Zaher and S. D. Mcarthur, A multi-agent fault detection system for wind turbine defect recognition and diagnosis, IEEE Lausanne PowerTech Proceedings, pp.22-27, 2007.

A. Zaher, S. D. Mcarthur, D. G. Infield, and Y. Patel, Online wind turbine fault detection through automated SCADA data analysis, Wind Energy, vol.12, issue.6, pp.574-593, 2009.

J. Li, X. Lei, H. Li, and L. Ran, Normal Behavior Models for the Condition Assessment of Wind Turbine Generator Systems. Electric Power Components and Systems, vol.42, pp.1201-1212, 2014.

Z. Zhang, Comparison of data-driven and model-based methodologies of wind turbine fault detection with SCADA data, Proceedings of the 2014 European Wind Energy Conference-EWEA 2014, 2014.

G. Shen-yin, H. R. Wang, and . Karimi, Data-driven design of robust fault detection system for wind turbines, Mechatronics, vol.24, issue.4, pp.298-306, 2014.

W. Chen, S. X. Ding, A. Haghani, A. Naik, A. Q. Khan et al., Observer-based fdi schemes for wind turbine benchmark, IFAC Proceedings Volumes, vol.44, pp.7073-7078, 2011.

L. Wang and C. Wen, Fault diagnosis of wind turbine blade based on robust residual error design, 2016.

, Chinese Control and Decision Conference (CCDC), pp.574-577, 2016.

Y. Liu and D. L. Yu, Robust fault detection for wind turbine systems, 20th International Conference on Automation and Computing, pp.38-42, 2014.

A. B. Borchersen and M. Kinnaert, Model-based fault detection for generator cooling system in wind turbines using SCADA data, Wind Energy, vol.19, issue.4, p.1852, 2016.

S. Butler, Prognostic Algorithms for Condition Monitoring and Remaining Useful Life Estimation, 2012.

D. Astolfi, F. Castellani, and L. Terzi, Fault prevention and diagnosis through SCADA temperature data analysis of an onshore wind farm. Diagnostyka, 15, 2014.

B. Boucher, Lowering the cost of project using simple analysis of SCADA data-a real case example, Annual Conference of the Prognostics and Health Management Society, 2013.

A. Lebranchu, S. Charbonnier, C. Bérenguer, and F. Prevost, Using SCADA data for fault detection in wind turbines: local internal model vs distance to a wind farm reference, Proc. of the 4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO 2014), 2014.

P. Cambron, C. Masson, A. Tahan, and F. Pelletier, Control chart monitoring of wind turbine generators using the statistical inertia of a wind farm average, Renewable Energy, vol.116, pp.88-98, 2018.

J. Tautz-weinert and S. J. Watson, Using SCADA data for wind turbine condition monitoring-a review, IET Renewable Power Generation, vol.11, issue.4, pp.382-394, 2017.

H. L. , Van Trees. Detection, Estimation, and Modulation Theory, Part I, 2001.