Title: Real time sharing method of panoramic data of substation equipment based on RAFT algorithm

Authors: Chengjie Cao; Jiaqi Zheng; Yifei Fan; Fangyuan Tian; Darui He

Addresses: Economics and Technological Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing, 210009, China ' Economics and Technological Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing, 210009, China ' Economics and Technological Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing, 210009, China ' Economics and Technological Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing, 210009, China ' Economics and Technological Research Institute, State Grid Jiangsu Electric Power Co., Ltd., Nanjing, 210009, China

Abstract: In order to solve the problems of low consistency and security in traditional data sharing methods, this paper designs a real-time sharing method of panoramic data of substation equipment based on RAFT algorithm. First, analyse the data generation process, and collect the panoramic data of the device in real time and quickly according to the location and environment of different devices. Then, the physical and logical relationship model between panoramic data is constructed, and the similarity data pair matrix is used to ensure the uniqueness of the data and complete the data preprocessing. Finally, RAFT algorithm is used to copy the data state, determine the data sharing node, and determine the degree of association between panoramic data through the weighted map, so as to achieve real time sharing of panoramic data in the same area. The experimental results show that the security factor and consistency factor can be guaranteed to be about 0.98 in the sharing process.

Keywords: RAFT algorithm; substation equipment; panoramic data; data sharing; device image.

DOI: 10.1504/IJRIS.2024.143159

International Journal of Reasoning-based Intelligent Systems, 2024 Vol.16 No.5, pp.375 - 382

Received: 06 Jan 2023
Accepted: 21 Mar 2023

Published online: 05 Dec 2024 *

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