Online monitoring of tool chatter in turning based on ensemble empirical mode decomposition and Teager Filter

Online monitoring of acquired vibration signals of the cutting tool can help in predicting the severity of chatter. In the past, researchers have reported that the signals recorded using various types of sensors are usually contaminated with background noise and other disturbances. Processing these contaminated signals results in inappropriate feature extraction. Hence, for predicting the exact nature of chatter it is required to identify: (1) Best suitable sensor for recording the chatter signal, (2) nature of the recorded signals, (3) appropriate technique to filter out the contamination, (4) applying suitable technique to identify chatter frequency and safe cutting zone. In the present work, a theoretical analysis has been done to extract the frequency pertaining to chatter. Moreover, experiments have been performed and a suitable signal pre and post-processing techniques have been adopted to identify the chatter frequency. It has been found that the variation between the theoretical and experimental values is nominal. Furthermore, the safe cutting zone has been identified theoretically as well as experimentally for a given range of input cutting parameters.