On-line chatter detection using servo motor current signal in turning

查看全文 作　　者：LIU [1]HongQil;CHEN [1]QmgHa;LI [1,2]Bin;MAO [1]XinYong;MAO [2]KuanMin;PENG [1]FangYu

机构地区：[1]National NC System Engineering Research Center, Huazhong University of Science &Technology, Wuhan 430074, China;[2]State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science &Technology, Wuhan 430074, China

出　　处：《Science China(Technological Sciences)》索引2011年第54卷第12期,共11页

基　　金：supported by the Major State Basic Research Development of China (Grant No. 2011CB706803);National Natural Science Foundation of China (Grant No. 50875098);Important National Science & Technology Specific Projects of China (Grant No. 2009ZX04014-024) 摘　　要：Chatter often poses limiting factors on the achievable productivity and is very harmful to machining processes. In order to avoid effectively the harm of cutting chatter,a method of cutting state monitoring based on feed motor current signal is proposed for chatter identification before it has been fully developed. A new data analysis technique,the empirical mode decomposition(EMD),is used to decompose motor current signal into many intrinsic mode functions(IMF) . Some IMF's energy and kurtosis regularly change during the development of the chatter. These IMFs can reflect subtle mutations in current signal. Therefore,the energy index and kurtosis index are used for chatter detection based on those IMFs. Acceleration signal of tool as reference is used to compare with the results from current signal. A support vector machine(SVM) is designed for pattern classification based on the feature vector constituted by energy index and kurtosis index. The intelligent chatter detection system composed of the feature extraction and the SVM has an accuracy rate of above 95% for the identification of cutting state after being trained by experimental data. The results show that it is feasible to monitor and predict the emergence of chatter behavior in machining by using motor current signal. 关键词：电流信号伺服电机在线检测国际货币基金组织数据分析技术经验模式分解固有模态函数智能检测系统

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On-line chatter detection using servo motor current signal in turning

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