A novel approach for chatter online monitoring using coefficient of variation in machining process

Chatter is one form of severe self-excited vibration in machining process which leads to many machining problems. In this paper, a new method of chatter identification is proposed. During the machining process, the acceleration signal of vibration is obtained and the time domain root mean square value of the acceleration is calculated every proper segment, through which the real-time acceleration root mean square (RMS) sequence is obtained. Then, the coefficient of variation (i.e., the ratio of the standard deviation to the mean, CV) of the RMS sequence is defined as the indicator for chatter identification. The milling experiment shows that CV can well distinguish the state (stable or chatter) of the machining process. The proposed method has a quantitative and dimensionless indicator, which works for different machining materials and machining parameters, and even can be expected to work in a wider range condition, such as different machine tool and cutting method. This paper also designs a fast algorithm of CV, making it an ideal candidate for online monitoring system.