计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 667-672.doi: 10.11896/jsjkx.200100091
禹鑫燚, 施甜峰, 唐权瑞, 殷慧武, 欧林林
YU Xin-yi, SHI Tian-feng, TANG Quan-rui, YIN Hui-wu, OU Lin-lin
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。
中图分类号:
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