Paper
5 June 2024 Defect detection of voltmeter in distributed electricity room based on improved deformable DETR
Author Affiliations +
Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 1316334 (2024) https://doi.org/10.1117/12.3030256
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China
Abstract
Voltmeter defect detection is a critical component in the calibration pipeline of electric meters. Traditional calibration methods heavily rely on manual inspection, resulting in time-consuming procedures with high rates of misjudgment. The scarcity of authentic samples containing defects poses challenges in constructing a sufficiently abundant dataset for defect samples. However, current Deformable DETR demonstrates suboptimal performance on small-scale datasets. One factor contributing to its underperformance on small-scale datasets is the excessive redundancy present in queries within the encoder, posing challenges for the model to effectively concentrate on objects. Moreover, the Hungarian matching in Deformable DETR results in a scarcity of positive examples, which hampers convergence speed. This paper introduces enhancements to Deformable DETR, including a sparse encoder and a hybrid matching mechanism, aimed at resolving the slow convergence problem on small-scale datasets. Finally, extensive experiments on our dataset validate the superior effectiveness of our proposed method, achieving the best performance in defect detection.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Haiming Gong, Mengen Sun, Xiangge Guo, Yi Wu, Wei Wang, and Jie Zheng "Defect detection of voltmeter in distributed electricity room based on improved deformable DETR", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 1316334 (5 June 2024); https://doi.org/10.1117/12.3030256
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KEYWORDS
Deformation

Defect detection

Education and training

Object detection

Ablation

Performance modeling

Calibration

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