Application of edge computing technology in dynamic diagnosis of power supply equipment of underwater junction box

Ping Sun

doi:10.1117/12.2637115

15 June 2022 Application of edge computing technology in dynamic diagnosis of power supply equipment of underwater junction box

Ping Sun

Author Affiliations +

Proceedings Volume 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022); 122850S (2022) https://doi.org/10.1117/12.2637115
Event: International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 2022, Zhuhai, China

Abstract

The junction box is the key subsystem responsible for power conversion, distribution and data transmission in the seabed observation network system. The on-line monitoring and intelligent diagnosis device of power conversion equipment, the core component of the junction box, is used as the edge agent to complete the local analysis and processing of equipment operation, alarm, action and other information, so as to realize the analysis of equipment operation status and dynamic diagnosis of abnormal conditions. The system architecture scheme of dynamic diagnosis technology of junction box equipment based on edge computing is proposed. This paper expounds the implementation method of dynamic diagnosis technology of edge agent for junction box equipment communication status, secondary circuit, voltage / current, pilot channel, device self-test and other data, and explores the key technologies of edge computing self-tuning and scalability. It can realize the dynamic diagnosis of the equipment status of the junction box, real-time acquisition of working conditions, early warning of abnormal status and accurate positioning of defects. Comprehensively promote the transformation of junction box equipment operation and maintenance to research and judgment based on data and intelligence, and improve the reliability of the equipment.

Citation Download Citation

Ping Sun "Application of edge computing technology in dynamic diagnosis of power supply equipment of underwater junction box", Proc. SPIE 12285, International Conference on Advanced Algorithms and Neural Networks (AANN 2022), 122850S (15 June 2022); https://doi.org/10.1117/12.2637115

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