A novel transformer-enhanced and acoustic-based approach for wind turbine blade fault detection with integrated system implementation-Reference-Cited by-同舟云学术

A novel transformer-enhanced and acoustic-based approach for wind turbine blade fault detection with integrated system implementation

Published:2024-03-24 Issue: Volume: Page:1-30
ISSN:0954-4828
Container-title:Journal of Engineering Design
language:en
Short-container-title:Journal of Engineering Design

Author:

Li Zeqiang¹²,Zhao Yang¹²,Zhang Yanjie³,Li Xinxin²,Bu Lingguo¹²

Affiliation:

1. Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, People’s Republic of China

2. School of Software, Shandong University, Jinan, People’s Republic of China

3. Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, People’s Republic of China

Funder

Natural Science Foundation of Shandong Province

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09544828.2024.2332122

Reference43 articles.

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2. Acoustical Damage Detection of Wind Turbine Blade Using the Improved Incremental Support Vector Data Description;Chen Bin;Renewable Energy,2020

3. Acoustic-Signal-Based Damage Detection of Wind Turbine Blades—A Review

4. Dosovitskiy Alexey Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold and Sylvain Gelly. 2020. “An image is worth 16(16 words: Transformers for image recognition at scale.” arXiv preprint arXiv:2010.11929.

5. Damage detection techniques for wind turbine blades: A review