Anomaly Detection on Small Wind Turbine Blades Using Deep Learning Algorithms

Anomaly Detection on Small Wind Turbine Blades Using Deep Learning Algorithms

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated...

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Bibliographic Details
Main Authors: Bridger Altice, Edwin Nazario, Mason Davis, Mohammad Shekaramiz, Todd K. Moon, Mohammad A. S. Masoum
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
deep learning
convolutional neural networks
small wind turbine blades
damage detection
transfer learning
VGG-19
Online Access:https://www.mdpi.com/1996-1073/17/5/982

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https://www.mdpi.com/1996-1073/17/5/982

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