基于Spark的设备状态数据实时处理系统设计  

Design of real-time data processing system of device status based on Spark

作　　者：李程文 Li Chengwen(Foshan Polytechnic,Foshan 528137,China)

机构地区：[1]佛山职业技术学院,广东佛山528137

出　　处：《无线互联科技》2022年第24期68-70,共3页Wireless Internet Technology

基　　金：广东省普通高校青年创新人才项目,项目编号:2020KQNCX213;中国高校产学研创新基金——新一代信息技术创新项目,项目编号:2020ITA03037。

摘　　要：工业革命后,设备故障的监测及诊断应运而生。故障诊断技术较为滞后,往往需要等故障发生后才能进行诊断和修复。为了实现对设备状态数据的实时采集、分析、预测和可视化,文章基于Spark设计实现了一种设备状态实时分析和预测系统,能够高效地实时数据接入、传输、计算校验和存储。该系统具有实时获取设备状态数据、实时分析数据、实时预测设备运行状态等特点,能够帮助企业及时对生产设备运行状态进行监测,从而减少生产设备的突发性停机与事故,减少生产设备运行和维护成本,提高了企业的生产效益。After the industrial Revolution, equipment fault monitoring and diagnosis came into being. However, the fault diagnosis technology is lagging behind, and it is often necessary to wait for the occurrence of fault before diagnosed and repaired. In order to realize real-time acquisition, analysis, prediction and visualization of device status data, this paper designs and implements a real-time analysis and prediction system of equipment status based on spark, which can realize efficient real-time data access, transmission, calculation, verification and storage. The system has the characteristics of real-time acquisition of equipment status data, real-time analysis data and real-time prediction of equipment operation status. It can help enterprises to timely monitor the operation status of production equipment, thereby reducing the sudden downtime and accidents of production equipment, reducing the operation and maintenance costs of production equipment and improving the production efficiency of enterprises.

关 键 词：实时 状态数据 Kafka SPARK 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TH17[自动化与计算机技术—计算机科学与技术]