A transfer learning approach for mitigating temperature effects on wind turbine blades damage diagnosis

Rezazadeh, Nima and Annaz, Fawaz and Jabbar, Waheb A. and Vieira Filho, Jozue and De Oliveira, Mario (2025) A transfer learning approach for mitigating temperature effects on wind turbine blades damage diagnosis. Structural Health Monitoring. ISSN 1475-9217

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Abstract

Data scarcity, coupled with environmental and operational variabilities (EOVs), poses substantial challenges to the generalisability and robustness of damage diagnostic methods for complex components such as wind turbine blades. This paper introduces a novel methodology, termed UCTRF, designed to tackle these challenges. UCTRF stands for Uniform manifold approximation and projection for dimensionality reduction, Capsule neural networks for advanced feature recognition, Transfer adaptive boosting for effective knowledge transfer, and Random Forest for nuanced instance weighting and classification. The UCTRF framework is uniquely suited to scenarios where feature distributions shift due to temperature variations, enabling robust knowledge transfer even in limited datasets. This innovative framework was rigorously evaluated on various temperature-affected datasets, achieving a 95% detection rate. These results underscore its effectiveness in preserving the structural integrity of wind turbines under challenging EOVs and constrained data availability. Additionally, the internal mechanism of the designed domain adaptation captures the alterations in instance weights between the source and target domains during the adjustment process, which can be utilised to analyse the impact of diverse instances on model performance and further refine the adaptation process.

Item Type:	Article
Identification Number:	10.1177/14759217241313350
Dates:	Date Event 1 January 2025 Accepted 30 January 2025 Published Online
Uncontrolled Keywords:	UMAP, CapsNet, structural health monitoring, domain adaptation, environmental conditions
Subjects:	CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-02 - mechanical engineering CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-08 - electrical and electronic engineering
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Engineering
Depositing User:	Gemma Tonks
Date Deposited:	10 Feb 2025 16:34
Last Modified:	10 Feb 2025 16:34
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16145

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