矿山电气设备在线监测与诊断系统的设计与实现
Design and Implementation of Online Monitoring and Diagnosis System for Mining Electrical Equipment
胡力友1
作者信息
- 1. 瓮福集团有限责任公司,贵州福泉 550500
- 折叠
摘要
设计了一个面向非金属矿山电气设备的在线监测与诊断系统.该系统实时在线监测关键电气设备的运行参数,并通过深度学习模型分析数据模式,实现潜在故障的诊断和预警.实验结果表明,该系统可有效提高电气设备异常监测和故障诊断的精度,降低突发故障风险,从而增强了非金属矿山生产的可靠性和安全性.
Abstract
This study designed an online monitoring and diagnostic system for electrical equipment in non-metallic mines.The system was designed to perform real-time online monitoring of operational parameters for key electrical equipment and utilize deep learning models to analyze data patterns,achieving the diagnosis and early warning of potential faults.Ex-perimental results indicated that the system significantly improves the accuracy of anomaly monitoring and fault diagnosis for electrical equipment,reduces the risk of sudden faults,and thus enhances the reliability and safety of non-metallic mine production.
关键词
非金属矿山/电气设备/监测/诊断Key words
non-metallic mine/electrical equipment/monitoring/diagnosis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据