Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

June 19, 2023


Pages

2443-2452


DOI

Article

Visual Operation and Maintenance Monitoring of Power System Data Network Based on Neural Network Model

Check for updates


Authors

Qinghua Zeng Affiliation:
Fujian branch of China Huadian Corporation LTD., Fuzhou, 350001, China.
, Jianbin Chen Affiliation:
Huadian (Fujian) Wind Power Co., Ltd, Fuzhou, 350001, China.
, Jingyao Liu Affiliation:
Huadian (Fujian) Wind Power Co., Ltd, Fuzhou, 350001, China.
, Haitao Cheng Affiliation:
State Grid Power Space Technology Co., Ltd, Beijing, 102209, China.
and Biao Zou Affiliation:
State Grid Power Space Technology Co., Ltd, Beijing, 102209, China.


Abstract

This paper introduces a communication network health monitoring technology and integrated operation management platform based on a power switching network. Firstly, network characteristics are described from technology, structure and service function. Separate regular communication networks. This paper studies a new condition-monitoring technology based on a power-switching network. This paper studies the topology of the AC power network. The condition of the network is carried out through the neural network. According to the perception results, an integrated operation management system is constructed to provide users with relevant data. This section describes the network fault status, fault diagnosis, and features of fiber hopping services. This paper offers some suggestions for operating and maintaining a power-switched network.


Keywords

Power switching optical network, Electric power communication network, State perception, Integrated operation and maintenance, 92B20


Citation

Zeng, Q., Chen, J., Liu, J., Cheng, H., & Zou, B. (2023). Visual operation and maintenance monitoring of power system data network based on neural network model. Applied Mathematics and Nonlinear Sciences, 8(1), 2443–2452. https://doi.org/10.2478/amns.2023.1.00425

Published by: Engineering Journals

Engineering Journals Logo