Damage identification of wind turbine blades based on deep learning and ultrasonic testing-Reference-Cited by-同舟云学术

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Damage identification of wind turbine blades based on deep learning and ultrasonic testing

Published:2024-02-28 Issue: Volume: Page:1-26
ISSN:1058-9759
Container-title:Nondestructive Testing and Evaluation
language:en
Short-container-title:Nondestructive Testing and Evaluation

Author:

Zhu Xinghan¹,Guo Zhenwu¹,Zhou Qiaojun¹,Zhu Chunxiang¹,Liu Tao²³,Wang Binrui¹

Affiliation:

1. School of Mechanical and Electrical Engineering, China Jiliang University, Zhejiang, China

2. School of Mechanical Engineering, Zhejiang University, Zhejiang, China

3. State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Zhejiang, China

Funder

China Zhejiang Provincial Science and Technology Department’s ‘top soldier’ and ‘leading wild goose’ R & D project

Funded by the corresponding author project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10589759.2024.2324373

Reference37 articles.

1. A Review of machine learning techniques for wind turbine’s fault detection, diagnosis, and prognosis

2. Defect detection and classification of offshore wind turbine rotor blades

3. Nacelle and tower effect on a stand-alone wind turbine energy output—A discussion on field measurements of a small wind turbine

4. Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks

5. Reverse supply network design for circular economy pathways of wind turbine blades in Europe

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. UAV based defect detection and fault diagnosis for static and rotating wind turbine blade: a review;Nondestructive Testing and Evaluation;2024-08-28

2. DFW-YOLO: YOLOv5-based algorithm using phased array ultrasonic testing for weld defect recognition;Nondestructive Testing and Evaluation;2024-07-27

3. Attention mechanism based on deep learning for defect detection of wind turbine blade via multi-scale features;Measurement Science and Technology;2024-07-18

4. Imaging method of surface defect using leaky Rayleigh wave with ultrasonic phased array;Nondestructive Testing and Evaluation;2024-07-16

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