摘 要
随着工业生产规模的不断扩大和自动化程度的提高，电气设备的安全运行成为保障生产连续性和人员安全的关键因素。本研究旨在探讨电气安全监测系统在工业生产中的应用，通过构建基于物联网技术的智能监测平台，实现对电气设备运行状态的实时监控与故障预警。采用先进的传感器网络、数据采集与处理技术，结合大数据分析算法，对电气设备的电流、电压、温度等关键参数进行全方位监测，建立完善的故障诊断模型。研究结果表明，该系统能够有效识别潜在电气安全隐患，提前预警并提供精准定位，将故障发生率降低了35%，平均维修响应时间缩短了42%。创新点在于实现了多源异构数据融合，提出了基于深度学习的故障预测模型，显著提高了系统的智能化水平和可靠性。
关键词：电气安全监测系统 物联网技术 故障预警
Abstract
With the continuous expansion of industrial production scale and the improvement of automation degree, the safe operation of electrical equipment has become a key factor to ensure the continuity of production and personnel safety. The purpose of this study is to explore the application of electrical safety monitoring system in industrial production, and realize the real-time monitoring and fault early warning of electrical equipment by building an intelligent monitoring platform based on the Internet of Things technology. Using advanced sensor network, data acquisition and processing technology, combined with big data analysis algorithm, the current, voltage, temperature and other key parameters of electrical equipment, to establish a perfect fault diagnosis model. The results show that the system can effectively identify potential electrical safety hazards, provide early warning and provide accurate positioning, reducing the failure rate by 35% and reducing the average maintenance response time by 42%. The innovation lies in the realization of multi-source heterogeneous data fusion and the fault prediction model based on deep learning, which significantly improves the intelligence level and reliability of the system.
Keyword:Electrical Safety Monitoring System Internet Of Things Technology Fault Early Warning
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3研究方法与技术路线 2
2电气安全监测系统架构设计 2
2.1系统总体架构规划 2
2.2关键技术选型分析 3
2.3数据采集与传输方案 3
2.4系统功能模块划分 4
3工业生产中的具体应用 4
3.1应用于生产设备监控 4
3.2生产流程安全管理 5
3.3故障预警与应急处理 5
3.4提升生产效率案例 6
4实施效果评估与展望 6
4.1安全性能提升分析 6
4.2经济效益评估方法 7
4.3应用中存在的问题 7
4.4未来发展方向探讨 8
结论 9
参考文献 10
致谢 11
随着工业生产规模的不断扩大和自动化程度的提高，电气设备的安全运行成为保障生产连续性和人员安全的关键因素。本研究旨在探讨电气安全监测系统在工业生产中的应用，通过构建基于物联网技术的智能监测平台，实现对电气设备运行状态的实时监控与故障预警。采用先进的传感器网络、数据采集与处理技术，结合大数据分析算法，对电气设备的电流、电压、温度等关键参数进行全方位监测，建立完善的故障诊断模型。研究结果表明，该系统能够有效识别潜在电气安全隐患，提前预警并提供精准定位，将故障发生率降低了35%，平均维修响应时间缩短了42%。创新点在于实现了多源异构数据融合，提出了基于深度学习的故障预测模型，显著提高了系统的智能化水平和可靠性。
关键词：电气安全监测系统 物联网技术 故障预警
Abstract
With the continuous expansion of industrial production scale and the improvement of automation degree, the safe operation of electrical equipment has become a key factor to ensure the continuity of production and personnel safety. The purpose of this study is to explore the application of electrical safety monitoring system in industrial production, and realize the real-time monitoring and fault early warning of electrical equipment by building an intelligent monitoring platform based on the Internet of Things technology. Using advanced sensor network, data acquisition and processing technology, combined with big data analysis algorithm, the current, voltage, temperature and other key parameters of electrical equipment, to establish a perfect fault diagnosis model. The results show that the system can effectively identify potential electrical safety hazards, provide early warning and provide accurate positioning, reducing the failure rate by 35% and reducing the average maintenance response time by 42%. The innovation lies in the realization of multi-source heterogeneous data fusion and the fault prediction model based on deep learning, which significantly improves the intelligence level and reliability of the system.
Keyword:Electrical Safety Monitoring System Internet Of Things Technology Fault Early Warning
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状综述 1
1.3研究方法与技术路线 2
2电气安全监测系统架构设计 2
2.1系统总体架构规划 2
2.2关键技术选型分析 3
2.3数据采集与传输方案 3
2.4系统功能模块划分 4
3工业生产中的具体应用 4
3.1应用于生产设备监控 4
3.2生产流程安全管理 5
3.3故障预警与应急处理 5
3.4提升生产效率案例 6
4实施效果评估与展望 6
4.1安全性能提升分析 6
4.2经济效益评估方法 7
4.3应用中存在的问题 7
4.4未来发展方向探讨 8
结论 9
参考文献 10
致谢 11
