摘要
为解决煤矿机电设备在运行过程中面临的故障诊断与预测问题,设计一种基于智能化技术的运行状态监测与故障诊断方法。实时采集设备运行数据,通过数据预处理、特征提取、故障诊断和故障预测等技术,可以提升诊断与预测的准确性。研究发现,所提方法在煤矿机电设备的应用中有效提升了故障诊断准确率与预测预警时间,显著降低误报率与漏报率。研究表明,结合数据驱动的智能化技术能够显著提高煤矿设备的运行效率与安全性,推动传统维护向智能化维护转型。
In order to solve the problem of fault diagnosis and prediction faced by coal mine electromechanical equipment during operation,an intelligent technology-based operation status monitoring and fault diagnosis method is designed.Real time collection of equipment operation data can improve the accuracy of diagnosis and prediction through techniques such as data preprocessing,feature extraction,fault diagnosis,and fault prediction.Research has found that the proposed method effectively improves the accuracy of fault diagnosis and prediction warning time in the application of coal mine electromechanical equipment,significantly reducing false alarm and missed alarm rates.Research has shown that combining data-driven intelligent technology can significantly improve the operational efficiency and safety of coal mine equipment,and promote the transformation from traditional maintenance to intelligent maintenance.
作者
李子耀
LI Ziyao(Shaanxi Coal Group Shenmu Ningtiaota Mining Co.,Ltd.,Yulin 719300)
出处
《现代制造技术与装备》
2026年第1期114-116,共3页
Modern Manufacturing Technology and Equipment
关键词
煤矿机电设备
智能化监测
故障诊断
故障预测
coal mine electromechanical equipment
intelligent monitoring
fault diagnosis
fault prediction
