Research on Safety Control Methods for Mechanical Operations in Substations Integrating Beidou RTK and AI_Vol. 3 No. 3 (JIEM 2025)_Journal of Industry and Engineering Management (ISSN: 2959-0612)

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Research on Safety Control Methods for Mechanical Operations in Substations Integrating Beidou RTK and AI

DOI: https://doi.org/10.62517/jiem.202503302

Author(s)

Bin Tang*, Jiankai Zou, Xiaoxin Wang, Xiangdong Lu, Zheng Li, Xiangyu Wang, Haosheng Yan, Junjie Guo, Weifeng Niu, Zihan Qiao

Affiliation(s)

State Grid Anyang Power Supply Company, Anyang, Henan, China *Corresponding Author

Abstract

As the level of mechanization in substation operations continues to improve, the complexity of the operational environment and potential risks have become increasingly evident. Traditional safety management measures are no longer sufficient to meet the modern power system's demand for efficient, precise, and safe operations. Beidou RTK (Real-Time Kinematic) high-precision positioning technology offers centimeter-level spatial positioning capabilities, while artificial intelligence (AI) technology has become increasingly mature in target recognition and behavior analysis. This paper addresses the safety management needs in mechanical operations at substations by proposing an intelligent safety management method that integrates Beidou RTK and AI. By establishing a dynamic perception system for the human-machine operational space, the method enables real-time identification of the locations and behaviors of personnel and machinery, as well as dynamic risk assessment. Additionally, this paper designs an intelligent warning and intervention mechanism based on integrated data to ensure effective control before potential hazards occur. Research indicates that this integrated method has the potential to enhance operational safety, precision, and management intelligence levels, providing an effective technical pathway for future intelligent maintenance of substations.

Keywords

Beidou RTK; Artificial Intelligence; Substation; Mechanical Operations; Safety Management; Intelligent Warning

References

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