物联网下智能制造设备故障预测分析  

Equipment failure prediction analysis for intelligent manufacturing under the Internet of Things

作　　者：赵军富 靳永胜 李建军[3] ZHAO Junfu;JIN Yongsheng;LI Jianjun(Engineering&Training Center,Inner Mongolia University of Science&Technology,Baotou 014010,China;Inner Mongolia Mengniu Dairy Group Company Limited,Hohhot 010000,China;Information Engineering School,Inner Mongolia University of Science&Technology,Baotou 014010,China)

机构地区：[1]内蒙古科技大学工程训练中心,内蒙古包头014010 [2]内蒙古蒙牛乳业(集团)股份有限公司,内蒙古呼和浩特0010000 [3]内蒙古科技大学信息工程学院,内蒙古包头014010

出　　处：《内蒙古科技大学学报》2023年第2期123-127,共5页Journal of Inner Mongolia University of Science and Technology

基　　金：内蒙古自治区教育科学规划课题资助项目(NGJGH2021159);内蒙古自治区自然科学基金资助项目(2022MS06009)。

摘　　要：针对生产企业设备故障导致生产效率低下的问题,应用物联网技术对生产过程实现实时监控,展示生产过程实时运行状况,预测未来生产设备可能发生的故障.提出一种应用物联网框架的设备故障预测分析实时监控系统,该系统通过生产车间现场布置的各式传感器实时采集设备运行数据,并将这些数据传递到故障预测平台系统,通过SERENA数据驱动方法处理数据来进行设备故障预测分析.通过一个家电生产线的案例分析,验证了预测分析方法的合理性,实现对设备的运行状况、故障预警和设备退化过程的实时监控,保证制造型企业的生产设备健康运行,降低宕机率,提高生产效率.To address the problem of low productivity due to equipment failure in manufacturing enterprises,Internet of Things technology was applied to achieve real-time monitoring of the production process,to show the real-time operation status of the production process,and to predict the possible future failure of production equipment.We proposed a real-time monitoring system for equipment failure prediction and analysis using the IoT framework.The system collects equipment operation data in real time through various sensors arranged on the production floor and transmits these data to the failure prediction platform system,which processes the data through the SERENA data-driven method to perform equipment failure prediction and analysis.Through a case study of a home appliance production line,the system verifies the rationality of the predictive analysis method,realizes real-time monitoring of equipment operation,fault warning and equipment degradation process,ensures healthy operation of production equipment in manufacturing enterprises,reduces downtime rate and improves productivity.

关 键 词：物联网 数据分析 预测分析 智能制造 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]