Title: Dynamic fault diagnosis means of the power message system based on big data

Authors: Dong He; Tong Chen; Haichao Huang; Weihao Qiu; Yize Tang; Jinxia Jiang

Addresses: State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China ' State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China ' State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China ' State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China ' State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China ' State Grid ZheJiang Electric Power Corporation Information and Telecommunication Branch, Zhejiang 310000, China

Abstract: Aiming at the poor fault diagnosis ability of traditional power information system, a dynamic fault diagnosis method based on big data for power information system is proposed. Firstly, the original fault information of power information system is sampled, and the collected fault characteristic data are reconstructed by multi feature and information fitting. Then, the attribute distribution detection and big data mining are carried out for the fault dynamic characteristics of power information system. According to the high-order spectrum feature distribution of the extracted power information system fault signals, the dynamic fault diagnosis and fuzzy clustering analysis are carried out for the power information system, and the fault diagnosis is optimised according to the classification results. The simulation results show that the dynamic fault diagnosis accuracy of power information system is high, the fault sample detection results are accurate and reliable, and the dynamic fault detection ability is improved.

Keywords: big data; electricity message system; fault; dynamic diagnosis; detection.

DOI: 10.1504/IJICT.2022.119320

International Journal of Information and Communication Technology, 2022 Vol.20 No.1, pp.83 - 96

Received: 14 May 2020
Accepted: 16 Jul 2020

Published online: 01 Dec 2021 *

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