A novel industrial multimedia: rough set based fault diagnosis system used in CNC grinding machine
A novel industrial multimedia: rough set based fault diagnosis system used in CNC grinding machine
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一种新型工业多媒体：基于粗糙集的数控磨床故障诊断系统
DOI：
10.1007/s11042-016-3878-0
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发表时间：
2017-10
期刊：
影响因子：
--
通讯作者：
Xiangke Tian
中科院分区：
文献类型：
--
作者：
Rongyong Zhao;Cuiling Li;Xiangke Tian
多媒体技术在数控磨床设计中的应用越来越广泛，自诊断系统是其中不可缺少的一部分。为充分利用多媒体技术，解决数控磨床自诊断模块中诊断知识缺乏的问题，设计了基于振动在线监测的数控磨床故障诊断知识发现与决策支持模型。分析了数控磨床故障诊断的特点。然后引入粗糙集理论对影响故障诊断的冗余信息进行约简，从而发现规则形式的故障诊断知识。基于粗糙集支持冗余信息约简的理论优势，提出了一种现代数控磨床故障诊断模块的决策支持模型，该模型易于从维修和故障诊断记录中发现诊断知识，并应用于某型号磨床故障诊断的工程实例。通过对故障诊断过程的工程解释，发现了对故障诊断有用的知识。通过与其他典型诊断方法的性能比较，验证了基于粗糙集理论的决策支持模型的有效性和优越性。本文为现代数控磨床故障诊断模块的开发提供了一种融合粗糙集理论和信息技术的多媒体解决方案，为其他现代机床故障诊断系统的构建提供了理论和技术参考。
Multimedia technologies are increasingly used in design of CNC grinding machines.The self-diagnosis system is a necessary part. To makeuse of multimediaand solve the problem about the lack of diagnosis knowledge included in the self-diagnosis module used in CNC grinding machines, this paper addresses the fault diagnosis knowledge discovery and the decision support model for fault diagnosis designed in a CNC grinding machine based on online vibration monitoring. The fault diagnosis characteristics of CNC grinding machine are analyzed first. Then the rough set theory is introduced to reduce the redundant information affecting fault diagnosis, thereby discover the fault diagnosis knowledge in the form of rules. Further, this paper proposes a decision support model of fault diagnosis module for modern CNC grinding machine, based on the theory advantages of redundant information reduction supported by rough set, being easy to find the diagnosis knowledge in the maintenance and faultdiagnosisrecords.Themodelisappliedintoanengineeringexampleoffaultdiagnosisfor a given type of grinding machine. Useful knowledge of fault diagnosis is discovered with the engineering interpretation of fault diagnosis process. The performance comparison with other typical diagnosis methods verifies the validity and advantage of the proposed decision support model based on rough set theory. This paper provides a multimedia solution integrated with rough set theory and information technology for diagnosis module developed in modern CNC grinding machines, and can be a theoretical and technical reference to build fault diagnosis systems used in other modern machines..
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