Research on fault diagnosis and maintenance of NC machine tools based on combination of dynamic and static data

机译：基于动静数据相结合的数控机床故障诊断与维修研究

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摘要

The method of fault diagnosis and maintenance for NC machine tools is established in this paper. The method combines the static data (reliability) and dynamic data (online monitoring) with the RCM technology. Take a certain NC machine tools as an example to verify the feasibility of the method. This method is used to realize the fault diagnosis and provide the maintenance strategy. RCM technology based on condition monitoring and fault diagnosis is of great significance to improve the maintenance efficiency of NC machine tools and optimize the maintenance resources.

机译：建立了数控机床的故障诊断与维护方法。该方法将静态数据（可靠性）和动态数据（在线监视）与RCM技术结合在一起。以某数控机床为例，验证了该方法的可行性。该方法用于实现故障诊断并提供维护策略。基于状态监测和故障诊断的RCM技术对于提高数控机床的维修效率和优化维修资源具有重要意义。

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来源
《2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference》|2017年|1554-1557|共4页
会议地点 Chengdu(CN)
作者
Huijuan Hao; Maoli Wang; Yongwei Tang;
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作者单位

Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center(National Supercomputer Center in Jinan), Jinan, China;

Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center(National Supercomputer Center in Jinan), Jinan, China;

Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center(National Supercomputer Center in Jinan), Jinan, China;

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会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Fault diagnosis; Computer numerical control; Tools; Circuit faults; Vibrations; Condition monitoring;

机译：故障诊断;计算机数控;工具;电路故障;振动;状态监测;;

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专利

1. NC Machine Tools Fault Diagnosis Based on Kernel PCA and k-Nearest Neighbor Using Vibration Signals [J] . Zhou Yuqing, Sun Bingtao, Li Fengping, Shock and vibration . 2015,第PTa5期

机译：基于核PCA和k最近邻的振动信号数控机床故障诊断
2. NC Machine Tools Fault Diagnosis Based on Kernel PCA andk-Nearest Neighbor Using Vibration Signals [J] . ZhouYuqing, SunBingtao, LiFengping, Shock and vibration . 2015,第1a2期

机译：基于核PCA和k近邻的振动信号数控机床故障诊断
3. Intelligent fault diagnosis using rough set method and evidence theory for NC machine tools [J] . Xin-Hua Yao, Jian-Zhong Fu, Zi-Chen Chen International Journal of Computer Integrated Manufacturing . 2009,第5期

机译：基于粗糙集和证据理论的数控机床故障智能诊断
4. Research on fault diagnosis and maintenance of NC machine tools based on combination of dynamic and static data [C] . Huijuan Hao, Maoli Wang, Yongwei Tang IEEE Information Technology, Networking, Electronic and Automation Control Conference . 2017

机译：基于动态和静态数据组合的NC机床故障诊断与维护研究
5. Internal Fault Diagnosis of MMC-HVDC Based on Classification Algorithms in Machine Learning [D] . Jin, Tianyi. 2019

机译：基于机器学习分类算法的MMC-HVDC的内部故障诊断
6. Big Data Approach to Batch Process Monitoring: Simultaneous Fault Detection and Diagnosis Using Nonlinear Support Vector Machine-based Feature Selection [O] . Melis Onel, Chris A. Kieslich, Yannis A. Guzman, -1

机译：大数据方法用于批处理过程监控：使用基于非线性支持向量机的特征选择同时进行故障检测和诊断
7. NC Machine Tools Fault Diagnosis Based on Kernel PCA andk-Nearest Neighbor Using Vibration Signals [O] . Zhou Yuqing, Sun Bingtao, Li Fengping, 2015

机译：NC机床基于内核PCA ANDK最近邻居使用振动信号的故障诊断

Research on fault diagnosis and maintenance of NC machine tools based on combination of dynamic and static data

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