基于深度学习的通信电源热插拔保护系统设计  

Design of Hot Swap Protection System of Communication Power Supply Based on Deep Learning

作　　者：朱超 魏刚 ZHU Chao;WEI Gang(Zhenjiang Power Supply Branch of State Grid Jiangsu Electric Power Co.,Ltd.,Zhenjiang 212001,China)

机构地区：[1]国网江苏省电力有限公司镇江供电分公司,江苏镇江212001

出　　处：《通信电源技术》2024年第12期112-114,共3页Telecom Power Technology

摘　　要：在现代通信系统中,电源的稳定与安全性对系统性能至关重要。文章设计一种基于深度学习的通信电源热插拔保护系统,以提高故障诊断的准确性和响应速度。通过构建和训练特定的神经网络模型,系统能够实时监测并预测潜在的故障,对通信电源进行有效保护,缩短系统中断时间,提升通信系统的整体可靠性。研究结果表明,该保护系统在实际应用中的性能显著优于传统保护技术,证实了深度学习技术在通信电源保护领域的应用潜力与实用价值。In modern communication system,the stability and security of power supply are very important to the system performance.This paper designs a hot swap protection system for communication power supply based on deep learning to improve the accuracy and response speed of fault diagnosis.By constructing and training a specific neural network model,the system can monitor and predict potential faults in real time,effectively protect the communication power supply,shorten the interruption time of the system and improve the overall reliability of the communication system.The research results show that the performance of the protection system in practical application is significantly better than the traditional protection technology,which confirms the application potential and practical value of deep learning technology in the field of communication power protection.

关 键 词：深度学习 通信电源 热插拔保护系统 故障诊断 

分 类 号：TN86[电子电信—信息与通信工程]