Wind turbine fault detection and classification by means of image texture analysis-Reference-Cited by-同舟云学术

Wind turbine fault detection and classification by means of image texture analysis

Published:2018-07 Issue: Volume:107 Page:149-167
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Ruiz Magda^ORCID,Mujica Luis E.,Alférez Santiago,Acho Leonardo,Tutivén Christian,Vidal Yolanda,Rodellar José,Pozo Francesc

Funder

Spanish Ministry of Economy and Competitiveness

Catalonia Government

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference47 articles.

1. Data-driven fault detection and isolation scheme for a wind turbine benchmark;de Bessa;Renew. Energy,2016

2. Current-based mechanical fault detection for direct-drive wind turbines via synchronous sampling and impulse detection;Gong;IEEE Trans. Ind. Electron.,2015

3. Multi-fault detection and failure analysis of wind turbine gearbox using complex wavelet transform;Teng;Renew. Energy,2016

4. A survey on wind turbine condition monitoring and fault diagnosis – Part I: Components and subsystems;Qiao;IEEE Trans. Ind. Electron.,2015

5. A survey on wind turbine condition monitoring and fault diagnosis – Part II: Signals and signal processing methods;Qiao;IEEE Trans. Ind. Electron.,2015

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