Machining chatter is a major factor restricting machining quality and efficiency. Traditional chatter monitoring methods have shortcomings in rapid identification of early chatter. In this study, a wavelet packet energy kurtosis index using cutting sound pressure signals was proposed to monitor the early turning chatter. The vibration characteristics of the cutting process from stable to unstable state were analyzed. Wavelet packet was used to decompose the on-line sound pressure signal, obtaining the weak features of the early chatter. Based on wavelet packet energy of each node, the wavelet packet energy kurtosis index was constructed to characterize the incubation period of chatter, and the target frequency band energy ratio was introduced to identify the developing state of chatter. The mapping relationship between the chatter evolution and the signal characteristics has been determined. Finally, the experimental results show that the monitoring method enables identifying the chatter evolution process accurately, which will help to increase the response time for the subsequent chatter control actions.
|Translated title of the contribution||A study on early chatter monitoring based on energy kurtosis index of acoustic signals|
|Original language||Chinese (Traditional)|
|Number of pages||6|
|Journal||Zhendong yu Chongji/Journal of Vibration and Shock|
|Publication status||Published - 28 Oct 2021|