Surface Damage Identification of Wind Turbine Blade Based on Improved Lightweight Asymmetric Convolutional Neural Network
Wind turbine blades are readily damaged by the workplace environment and frequently experience flaws such as surface peeling and cracking. To address the problems of cumbersome operation, high cost, and harsh application conditions with traditional damage identification methods, and to cater to the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-05-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/10/6330 |