통계학적 변수를 이용한 엔드밀링의 채터 검출법

Chatter behavior in end-milling is both complex and closely related to the dynamic unbalanced malfunction phenomenon of the end-milling force; hence, it is difficult to clearly detect and diagnose this behavior using a cutting force. Therefore, this paper presents a new method for detecting chatter in end-milling operations using different stochastic variables such as average, residual, variance, and kurtosis variables. By comparing the histories and stochastic variables of the end-milling force using the fundamental end-milling property, the chatter characteristics can be reviewed and compared with other variables. Stochastic variable threshold values can therefore separate chatter and non-chatter states, and can be used reliably in the detection and prediction of chatter properties in end milling. KCI Citation Count: 0