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Energies 2016, 9(7), 520; doi:10.3390/en9070520

On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis

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 (Barcelona) 08930, Spain
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Academic Editor: Frede Blaabjerg
Received: 10 May 2016 / Revised: 16 June 2016 / Accepted: 30 June 2016 / Published: 5 July 2016
(This article belongs to the Collection Wind Turbines)
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Abstract

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. View Full-Text
Keywords: principal component analysis; hypothesis test; fault detection; sensor selection; FAST principal component analysis; hypothesis test; fault detection; sensor selection; FAST
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pozo, F.; Vidal, Y.; Serrahima, J.M. On Real-Time Fault Detection in Wind Turbines: Sensor Selection Algorithm and Detection Time Reduction Analysis. Energies 2016, 9, 520.

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