摘 要
随着电力系统规模的不断扩大和智能化技术的快速发展，传统电气设备运维管理方式已难以满足现代电网高效、可靠运行的需求，亟需构建一种智能化运维管理系统以提升设备管理效率与安全性。本研究旨在开发一套基于物联网、大数据分析及人工智能技术的电气设备智能化运维管理系统，通过实时监测、智能诊断与预测性维护实现对电气设备全生命周期的精细化管理。研究采用模块化设计思路，结合传感器网络数据采集、云计算处理以及边缘计算技术，构建了集状态感知、故障预警、性能评估于一体的综合管理平台。系统创新性地引入深度学习算法优化故障诊断模型，并通过多源异构数据融合提升决策准确性。
关键词：电气设备 智能化运维管理 物联网
Abstract
With the continuous expansion of the power system scale and the rapid development of intelligent technology, the traditional operation and maintenance management mode of electrical equipment has been difficult to meet the needs of efficient and reliable operation of the modern power grid, and it is urgent to build an intelligent operation and maintenance management system to improve the efficiency and security of equipment management. The study aims to develop a set of intelligent operation and maintenance management system for electrical equipment based on the Internet of Things, big data analysis and artificial intelligence technology, so as to realize the fine management of the whole life cycle of electrical equipment through real-time monitoring, intelligent diagnosis and predictive maintenance. The research adopts modular design idea, combined with sensor network data acquisition, cloud computing processing and edge computing technology, to build a comprehensive management platform integrating state perception, fault warning and performance evaluation. The system innovatively introduces the deep learning algorithm to optimize the fault diagnosis model, and improves the decision accuracy through multi-source heterogeneous data fusion.
Keyword:Electrical Equipment Intelligent Operation And Maintenance Management Internet Of Things
目 录
1绪论 1
1.1电气设备智能化运维的背景与意义 1
1.2国内外研究现状分析 1
1.3研究方法与技术路线 1
2智能化运维管理系统需求分析 2
2.1电气设备运维管理的核心需求 2
2.2智能化运维的功能需求分解 2
2.3数据采集与处理的需求设计 3
3智能化运维管理系统架构设计 3
3.1系统总体架构设计 3
3.2数据层设计与实现 4
3.3功能模块划分与逻辑关系 4
4智能化运维管理系统关键技术研究 5
4.1数据采集与传输技术研究 5
4.2故障诊断与预测算法分析 5
4.3系统安全性与可靠性保障 6
结论 6
参考文献 8
致谢 9
随着电力系统规模的不断扩大和智能化技术的快速发展，传统电气设备运维管理方式已难以满足现代电网高效、可靠运行的需求，亟需构建一种智能化运维管理系统以提升设备管理效率与安全性。本研究旨在开发一套基于物联网、大数据分析及人工智能技术的电气设备智能化运维管理系统，通过实时监测、智能诊断与预测性维护实现对电气设备全生命周期的精细化管理。研究采用模块化设计思路，结合传感器网络数据采集、云计算处理以及边缘计算技术，构建了集状态感知、故障预警、性能评估于一体的综合管理平台。系统创新性地引入深度学习算法优化故障诊断模型，并通过多源异构数据融合提升决策准确性。
关键词：电气设备 智能化运维管理 物联网
Abstract
With the continuous expansion of the power system scale and the rapid development of intelligent technology, the traditional operation and maintenance management mode of electrical equipment has been difficult to meet the needs of efficient and reliable operation of the modern power grid, and it is urgent to build an intelligent operation and maintenance management system to improve the efficiency and security of equipment management. The study aims to develop a set of intelligent operation and maintenance management system for electrical equipment based on the Internet of Things, big data analysis and artificial intelligence technology, so as to realize the fine management of the whole life cycle of electrical equipment through real-time monitoring, intelligent diagnosis and predictive maintenance. The research adopts modular design idea, combined with sensor network data acquisition, cloud computing processing and edge computing technology, to build a comprehensive management platform integrating state perception, fault warning and performance evaluation. The system innovatively introduces the deep learning algorithm to optimize the fault diagnosis model, and improves the decision accuracy through multi-source heterogeneous data fusion.
Keyword:Electrical Equipment Intelligent Operation And Maintenance Management Internet Of Things
目 录
1绪论 1
1.1电气设备智能化运维的背景与意义 1
1.2国内外研究现状分析 1
1.3研究方法与技术路线 1
2智能化运维管理系统需求分析 2
2.1电气设备运维管理的核心需求 2
2.2智能化运维的功能需求分解 2
2.3数据采集与处理的需求设计 3
3智能化运维管理系统架构设计 3
3.1系统总体架构设计 3
3.2数据层设计与实现 4
3.3功能模块划分与逻辑关系 4
4智能化运维管理系统关键技术研究 5
4.1数据采集与传输技术研究 5
4.2故障诊断与预测算法分析 5
4.3系统安全性与可靠性保障 6
结论 6
参考文献 8
致谢 9
