LAPSE:2019.0026
Published Article
LAPSE:2019.0026
On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis
Francesc Pozo, Yolanda Vidal, Josep M. Serrahima
January 7, 2019
In this paper, we address the problem of real-time fault detection in wind turbines. Starting from a data-driven fault detection method, the contribution of this paper is twofold. First, a sensor selection algorithm is proposed with the goal to reduce the computational effort of the fault detection method. Second, an analysis is performed to reduce the data acquisition time needed by the fault detection method, that is, with the goal of reducing the fault detection time. The proposed methods are tested in a benchmark wind turbine where different actuator and sensor failures are simulated. The results demonstrate the performance and effectiveness of the proposed algorithms that dramatically reduce the number of sensors and the fault detection time.
Keywords
FAST, Fault Detection, hypothesis test, principal component analysis, sensor selection
Suggested Citation
Pozo F, Vidal Y, Serrahima JM. On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis. (2019). LAPSE:2019.0026
Author Affiliations
Pozo F: Control, Dynamics and Applications (CoDAlab), Departament de Matemàtiques, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 6–12, Sant Adrià de Besòs (Barcelon [ORCID]
Vidal Y: Control, Dynamics and Applications (CoDAlab), Departament de Matemàtiques, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 6–12, Sant Adrià de Besòs (Barcelon [ORCID]
Serrahima JM: Control, Dynamics and Applications (CoDAlab), Departament de Matemàtiques, Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Campus Diagonal-Besòs (CDB), Eduard Maristany, 6–12, Sant Adrià de Besòs (Barcelon
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Journal Name
Energies
Volume
9
Issue
7
Article Number
E520
Year
2016
Publication Date
2016-07-05
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en9070520, Publication Type: Journal Article
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LAPSE:2019.0026
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doi:10.3390/en9070520
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Jan 7, 2019
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CC BY 4.0
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Jan 7, 2019
 
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Jan 7, 2019
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Original Submitter
Calvin Tsay
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