面向预测性维护的工业设备管理系统  

Industrial Equipment Management System for Predictive Maintenance

作　　者：禹鑫燚[1] 施甜峰 唐权瑞 殷慧武 欧林林[1] YU Xin-yi;SHI Tian-feng;TANG Quan-rui;YIN Hui-wu;OU Lin-lin(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)

机构地区：[1]浙江工业大学信息工程学院,杭州310023

出　　处：《计算机科学》2020年第S02期667-672,677,共7页Computer Science

基　　金：国家重点研发计划(2018YFB1308400)。

摘　　要：为了解决制造业中工业设备管理混乱、维护成本高昂等问题,以工业机器人、数控车床等工业设备为管理对象,开发面向预测性维护的设备管理系统。基于SpringBoot框架和Vue前后端分离模式对系统进行开发,降低其耦合性;根据实际生产需求设计设备管理模块,实现设备基础信息和生产数据的管理;并开发人机交互良好的前端界面,达到设备信息可视化管理的目的;整合多种数据库设计数据存储模块,解决系统不同数据种类的读写问题;基于Spark大数据处理框架设计设备维护模块,对设备实时数据进行在线分析,并使用机器学习回归算法对历史数据进行预测模型训练,实现设备状态的实时监控与剩余使用寿命的预测,达到设备预测性维护的目的。最后,通过工业机器人设备实验验证了所设计的管理系统的可行性。An industrial equipment management system for predictive maintenance is developed to solve the problems of chaotic equipment management and high maintenance costs in the manufacturing industry.The system is developed based on SpringBoot framework and Vue front-end separation mode that the coupling is reduced;the equipment management module is designed according to the actual production that realizes the basic information and production data management of the equipment.A good front-end interface for human-computer interaction is developed to achieve the purpose of visual management of equipment information.The data storage module is designed through integrating multiple databases to solve the problem of reading and writing different types of data in the system.The equipment maintenance module is designed based on the Spark big data processing framework to perform online analysis of equipment real-time data.In order to achieve the goal of predictive maintenance of equipment,machine learning regression algorithms are used to train predictive models on historical data to achieve real-time monitoring of equipment status and prediction of remaining life.Finally,the feasibility of the designed management system is verified by industrial robot equipment experiments.

关 键 词：设备管理 SPARK 机器学习 大数据处理 预测性维护 

分 类 号：TP315[自动化与计算机技术—计算机软件与理论]