Intelligent observer for fault detection and data recovery for small wind turbine

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.

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Publication Details

Journal
Logic Journal of IGPL
Published
2025-04-26
DOI
https://doi.org/10.1093/jigpal/jzaf026
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Intelligent observer for fault detection and data recovery for small wind turbine

Álvaro Michelena, Antonio Díaz-Longueira, Marta-María Álvarez-Crespo, Míriam Timiraos et al.
Logic Journal of IGPL
Machine Fault Diagnosis Techniques
article

Intelligent observer for fault detection and data recovery for small wind turbine

Álvaro Michelena, Antonio Díaz-Longueira, Marta-María Álvarez-Crespo, Míriam Timiraos, Óscar Fontenla-Romero, José Luis Calvo-Rolle
article en

Abstract

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.

Logic Journal of IGPLVol. 34(1)
Universidade da Coruña (ES)
Affordable and clean energy
Openalex Percentile: Top 31%
Machine Fault Diagnosis Techniques
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