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A Gramian Angular Field-Based Convolutional Neural Network Approach for Crack Detection in Low-Power Turbines from Vibration Signals

The detection of damage in wind turbine blades is critical for ensuring their operational efficiency and longevity. This study presents a novel method for wind turbine blade damage detection, utilizing Gramian Angular Field (GAF) transformations of vibration signals in combination with Convolutional...

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Principais autores: Angel H. Rangel-Rodriguez, Juan P. Amezquita-Sanchez, David Granados-Lieberman, David Camarena-Martinez, Maximiliano Bueno-Lopez, Martin Valtierra-Rodriguez
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2025-09-01
coleção:Information
Assuntos:
convolutional neural network
crack detection
deep learning
gramian angular field
vibration signals
wind turbine
Acesso em linha:https://www.mdpi.com/2078-2489/16/9/775
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