Research on industrial meter readings based on improved YOLOv8

Junyi Wu; Weizheng Wang; Lei Yang; Xuesong Ni; Liqin Tian

doi:10.1117/12.3031129

19 July 2024 Research on industrial meter readings based on improved YOLOv8

Junyi Wu, Weizheng Wang, Lei Yang, Xuesong Ni, Liqin Tian

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131815G (2024) https://doi.org/10.1117/12.3031129
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

With the rapid development of intelligent transformation in China's petrochemical industry, the intelligent inspection of oil and gas operation sites such as oil pumping stations has become a crucial initiative. The introduction of inspection robots for operation in complex environments and the application of intelligent methods for reading industrial instruments are particularly significant. This paper, utilizing deep learning approaches, presents an algorithm for the detection and recognition of readings on instruments applicable to many types of meters. The proposed algorithm achieves the intelligent inspection of power equipment. Additionally, a YOLOv8-based instrument detection method is introduced, incorporating improvements with GAM attention and a multiscale hierarchical decoupled head. This method effectively addresses challenges in instrument detection and recognition, including difficulties in instrument localization and low inference accuracy during the process.

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

Citation Download Citation

Junyi Wu, Weizheng Wang, Lei Yang, Xuesong Ni, and Liqin Tian "Research on industrial meter readings based on improved YOLOv8", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131815G (19 July 2024); https://doi.org/10.1117/12.3031129

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KEYWORDS

Object detection

Equipment

Detection and tracking algorithms

Performance modeling

Small targets

Target detection

Instrument modeling

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