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作 者:张新[1] ZHANG Xin(Shaoxing Vocational & Technical College Shaoxing, Zhejiang 312000)
出 处:《工业安全与环保》2021年第4期49-53,共5页Industrial Safety and Environmental Protection
基 金:国家科技型中小企业技术创新基金(13C26213302220)。
摘 要:以矿山机电设备运行数据采集为切入点研究矿山大数据技术应用。利用传感器采集数据,基于LoRaWAN物联网远程通信接入平台传输采集数据,构建起矿山机电设备状态数据采集系统,以大数据技术应用理念出发,设计与分析矿山机电设备云计算服务平台,实现对矿山设备运行状态的实时监测。通过对矿山设备工作数据的积累,结合矿山信息化系统的数据融合,借助大数据技术,对矿山设备运行大数据进行处理、分析、挖掘和可视化,实现了矿山机电设备各种异常状态和故障的预测与判别,以及多参数之间相互关系的分析与预测,为大数据技术在矿山开采领域中的应用和矿物开采效率的提高起到积极的作用。This paper studied the application of big data technology based on the operation data collection of mine mechanical and electrical equipment.Sensors were used to collect data and the mining mechanical and electrical equipment status data collection system was constructed based on loRaWAN internet of things remote communication access platform to transmit the collected data.Based on the application concept of big data technology,the mining mechanical and electrical equipment cloud computing service platform was designed and analyzed to realize the real-time monitoring of the operation status of mining equipment.Through the accumulation of the working data of mine equipment,combined with the data fusion of mine information system,the processing,analyzing,mining and visualizing the big data of mine equipment operation were carried out with the help of big data technology,which realized the prediction and discrimination of various abnormal states and faults of mine mechanical and electrical equipment,as well as the analysis and prediction of the relationship between multiple parameters,playing a positive role in the application of big data technology in the field of mining and the improvement of mineral mining efficiency.
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