文章基本信息

标题：A Force Monitoring Method Based on Built-in Sensors for Feed System of Computer Numerical Control Machine Tools
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作者：Guangsheng Chen ; Qingzhen Zheng
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2016
卷号：14
期号：3A
页码：345-352
DOI：10.12928/telkomnika.v14i3A.4429
语种：English
出版社：Universitas Ahmad Dahlan
摘要：As force has important influence to the performance and machining quality of machine tool during machining process, this paper proposed a method to monitor the load force of feed system using build-in sensor of the machine tools. To reduce the influence of noise caused by external disturbance and difference operation, a state observer based on Kalman filter that optimized values of force, velocity and displacement of feed system is adopted, and gain coefficient of the observer is obtained by recursive algorithm. To validate the effectiveness of the method, friction force testing experiments under no-load and force testing experiments under complex cutting conditions are performed respectively, the results show that data obtained by the method are effective, and this method significantly restrained the external noise and noise caused by difference operation. The method suits to on-line and real-time force monitoring in production without additional sensors.
其他摘要：As force has important influence to the performance and machining quality of machine tool during machining process, this paper proposed a method to monitor the load force of feed system using build-in sensor of the machine tools. To reduce the influence of noise caused by external disturbance and difference operation, a state observer based on Kalman filter that optimized values of force, velocity and displacement of feed system is adopted, and gain coefficient of the observer is obtained by recursive algorithm. To validate the effectiveness of the method, friction force testing experiments under no-load and force testing experiments under complex cutting conditions are performed respectively, the results show that data obtained by the method are effective, and this method significantly restrained the external noise and noise caused by difference operation. The method suits to on-line and real-time force monitoring in production without additional sensors.
关键词：Kalman filter;Feed system;Force monitoring;Built-in sensor