Enhanced Prediction Performance of Internal Defect Detection in Wind Turbine Blades on Thermography Using Deep Learning Models with Preprocessed Synthetic Data

Enhanced Prediction Performance of Internal Defect Detection in Wind Turbine Blades on Thermography Using Deep Learning Models with Preprocessed Synthetic Data

This study proposes a method for detecting internal defects in wind turbine blades using deep learning, eliminating the reliance on inspectors’ experiments. To address the class imbalance problem inherent in defect detection environments, synthetic thermographic datasets were generated using a synth...

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Bibliographic Details
Main Authors: Haemyung Chon, Daekyun Oh, Jackyou Noh
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
wind turbine blade
defect detection
internal defect
thermal inspection
deep learning
synthetic data
Online Access:https://www.mdpi.com/2076-3417/15/6/3042
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