An InceptionNet-based object detection algorithm for wind turbine inspection robot

Yanjun Qiao; Shouli Hao; Zhijian Wang; Zhiwei Kou; Xiaoming Cui; Zhe Kong

doi:10.1117/12.3035587

16 August 2024 An InceptionNet-based object detection algorithm for wind turbine inspection robot

Yanjun Qiao, Shouli Hao, Zhijian Wang, Zhiwei Kou, Xiaoming Cui, Zhe Kong

Proceedings Volume 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024); 132301L (2024) https://doi.org/10.1117/12.3035587
Event: Third International Conference on Machine Vision, Automatic Identification and Detection, 2024, Kunming, China

Abstract

Wind power has developed rapidly in recent years, and regular inspection of wind turbines can guarantee their normal operation. The use of inspection robots can improve inspection efficiency and reduce risks. The traditional way mainly relies on the manual operation of the UAV to search the wind turbines, which still has the problem of low efficiency. For the object search problem in aerial images, this paper proposes a wind turbine object detection algorithm based on the Inception Network, which uses artificial intelligence to extract wind turbine objects in the images. For the problem of excessive parameters in the baseline algorithm, this paper replaces the original backbone network to reduce the number of parameters. For the problem of overfitting, the paper adopts the strategy of Batch Normalization to improve the generalization ability. After the test using the NAIP dataset, the algorithm achieves the accuracy of 93.10% on the wind turbine object detection task. The results show that the object detection algorithm based on Inception Network can achieve better results and has certain robustness and generalization ability for objects in different environments.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yanjun Qiao, Shouli Hao, Zhijian Wang, Zhiwei Kou, Xiaoming Cui, and Zhe Kong "An InceptionNet-based object detection algorithm for wind turbine inspection robot", Proc. SPIE 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024), 132301L (16 August 2024); https://doi.org/10.1117/12.3035587

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KEYWORDS

Object detection

Wind turbine technology

Detection and tracking algorithms

Inspection

Education and training

Batch normalization

Overfitting

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