Milling chatter detection based on information entropy of interval frequency

Abstract

Chatter has been one of the most unfavorable issues during the milling, seriously affecting the machining efficiency, quality of machined surface. In this paper, considering the distribution characteristics of multiple chatter frequencies for milling process, a chatter detection method based on the information entropy of interval frequency (IFIE) is proposed. The matrix notch filter is first utilized to filter out the harmonics of spindle rotating frequency and possible colored noise components. Then the main components of filtered signals are estimated with a subspace-based technique. Specially, interval frequency (IF) that denotes the distance between estimated frequencies to the nearest harmonics of spindle rotating frequency is proposed, and then the chatter indicator IFIE is developed by constructing the histogram of IFs. Finally, the milling experiments under various conditions are utilized to validate the proposed methodology, and the results show that the chatter at early stage can be accurately and timely detected.