Díaz-Longueira, AntonioÁlvarez-Crespo, Marta MaríaMichelena, ÁlvaroTimiraos, MíriamFontenla-Romero, ÓscarCalvo-Rolle, José Luis2026-04-102026-04-102026-01-28Antonio Díaz-Longueira, Marta-María Álvarez-Crespo, Álvaro Michelena, Míriam Timiraos, Óscar Fontenla-Romero, José Luis Calvo-Rolle, Intelligent observer for fault detection and data recovery for small wind turbine, Logic Journal of the IGPL, Volume 34, Issue 1, February 2026, jzaf026, https://doi.org/10.1093/jigpal/jzaf0261368-9894https://hdl.handle.net/2183/47928Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] In this work, an intelligent observer is developed and implemented for fault detection and information retrieval in a small wind turbine. The intelligent observer will allow the detection of faults in the turbine’s energy generation, thanks to the estimation of the active power generated. This estimate will be compared with the real active power, measured by a real sensor, so that, if there is not a very high deviation between both values, the sensor measurement will be considered valid. However, when the difference between the estimated value and the real value exceeds a threshold, the sensor measurement will be replaced with the estimate. This threshold will be determined based on the operating point. The results obtained are satisfactory, with a correct estimation and detection of anomalies.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/Fault detectionAnomaly detectionGreen energyHybrid modeljournal articleopen access10.1093/jigpal/jzaf026