摘要
现有的视情维修系统研究中缺乏对处于正常运行阶段的设备因加工过程操作不当所引起的运行故障进行预测维修。为提高柔性制造系统的使用寿命及使用效率,提出预测与健康管理视情维修的体系结构,构建柔性制造系统视情维修系统的功能框图并分析其工作流程;通过对设备运行状态信息融合,借助人工智能推理对柔性制造系统的状态监测、健康评估和故障预测方法进行了具体分析。该方案能够实现柔性制造系统故障的提前预测和剩余寿命计算,具有重要的工业推广价值。
In view of the lack of the capacity of prediction maintenance in existing condition-based maintenance system research,and considering this situation that,in normal operation phase,with wrong operation,equipments malfunction also occurred,the system structure of a modified condition-based maintenance system based on failure prediction and health management was proposed to increase service life and efficiency of flexible manufacturing system.Functional block diagram of the modified condition-based maintenance system was established and workflow was elaborated.Using data fusion technology and artificial intelligence reasoning,condition monitoring,health assessment and failure prediction were all analyzed in detail.The failure can be predicted in advance adopting the modified condition-based system,and the residual life can be calculated.So it has promotion value in industry.
出处
《机床与液压》
北大核心
2012年第7期186-190,共5页
Machine Tool & Hydraulics
基金
淮海工学院自然科学基金项目(Z2008008)
关键词
故障预测
健康管理
神经网络
柔性制造系统
视情维修
Failure prediction
Health management
Neural networks
Flexible manufacturing system
Condition-based maintenance
