A method for transformer substation personnel behavior recognition based on improved AlphaPose algorithm

Lin Zou; Yubo Zhang; Xu Liu; Yufeng Lu; Chengwei Huang

doi:10.1117/12.3050093

8 November 2024 A method for transformer substation personnel behavior recognition based on improved AlphaPose algorithm

Lin Zou, Yubo Zhang, Xu Liu, Yufeng Lu, Chengwei Huang

Author Affiliations +

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134160U (2024) https://doi.org/10.1117/12.3050093
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

In recent years, the safety and efficiency of transformer substation operations have gained significant attention. Monitoring personnel behavior within these facilities is crucial for maintaining safety standards and optimizing performance. This paper presents a novel approach to personnel behavior recognition in transformer substations using an improved AlphaPose algorithm. By enhancing the AlphaPose algorithm with additional preprocessing steps, optimized model parameters, and integration with machine learning classifiers, our method achieves superior accuracy and robustness in recognizing various personnel activities. Experimental results demonstrate the effectiveness of the proposed method in real-world transformer substation environments.

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

Citation Download Citation

Lin Zou, Yubo Zhang, Xu Liu, Yufeng Lu, and Chengwei Huang "A method for transformer substation personnel behavior recognition based on improved AlphaPose algorithm", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134160U (8 November 2024); https://doi.org/10.1117/12.3050093

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