摘要
随着煤矿开采自动化水平的不断提高,采煤机的远程监控与故障诊断成为保障煤矿开采高效、稳定运行的关键。通过对采煤机运行环境与工作特点的分析,明确了系统的技术需求与性能要求。详细阐述了物联网架构与通信技术的选择、传感器网络的设计以及多源数据融合与状态监测方法的应用。基于大数据分析的故障预测方法和故障告警机制被用于提升系统的预警能力。系统实现了远程监控、实时数据处理与显示,并支持移动终端访问,为采煤机的智能化管理和维护提供了新的思路和技术参考。
With the continuous improvement of the automation level of coal mining,remote monitoring and fault diagnosis of coal mining machine have become the key to ensure efficient and stable operation of coal mining.This paper clarifies the technical requirements and performance requirements of the system through the analysis of the operating environment and working characteristics of coal mining machine.The selection of IoT architecture and communication technology,the design of sensor network,and the application of multi-source data fusion and status monitoring methods are elaborated in detail.Fault prediction methods and fault alarm mechanisms based on big data analysis are used to improve the early warning capability of the system.The system realizes remote monitoring,real-time data processing and display,and supports mobile terminal access,in order to provide new ideas and technical references for the intelligent management and maintenance of coal mining machine.
作者
王尚坤
王书亮
WANG Shangkun;WANG Shuliang(Production Service Branch,Xinwen Mining Group Co.,Ltd.,Tai'an,Shandong 271219,China)
出处
《自动化应用》
2025年第5期168-171,共4页
Automation Application
关键词
物联网
采煤机
远程监控
故障诊断
大数据分析
IoT
coal mining machine
remote monitoring
fault diagnosis
big data analysis
