基于深度学习的电气设备状态监测预警系统设计  

Design of an Electrical Equipment Condition Monitoring and Early Warning System Based on Deep Learning

作　　者：尚子新 李旭鹏 朱文静 闫悦涵 SHANG Zixin;LI Xupeng;ZHU Wenjing;YAN Yuehan(Xi′an Mingde Institute of Technology,School of Intelligent Manufacturing and Control Technology,Xi′an 710124,China;Xi′an Jiaotong University City College,School of Electrical Information,Xi′an 710018,China)

机构地区：[1]西安明德理工学院智能制造与控制技术学院,陕西西安710124 [2]西安交通大学城市学院电气信息学院,陕西西安710018

出　　处：《电工技术》2025年第2期85-88,共4页Electric Engineering

摘　　要：电气设备状态监测与预警系统通过实时监测和预警机制保障设备的安全与稳定运行,因此提出了一种基于深度学习的电气设备状态监测预警系统方案,利用卷积神经网络和循环神经网络对电气设备的运行数据进行分析处理,实现了从数据采集、数据传输、数据预处理到模型构建和实时监测预警的全流程方案。所提方案有力提高了电气设备故障检测的准确性和及时性,确保了设备的高效运行和维护。The condition monitoring and early warning system for electrical equipment ensures the safety and stable operation of the equipment through real-time monitoring and early warning mechanisms.This paper proposes a design for an electrical equipment condition monitoring and early warning system based on deep learning.The system utilizes convolutional neural networks and recurrent neural networks to analyze and process the operation data of electrical equipment,achieving a complete process solution from data collection,data transmission,data preprocessing to model construction and real-time monitoring and early warning.The design of this system aims to improve the accuracy and timeliness of electrical equipment fault detection,ensuring the efficient operation and maintenance of the equipment.

关 键 词：深度学习 电气设备 监测预警 

分 类 号：TM62[电气工程—电力系统及自动化]