Identification of AE Signal for Tool Breakage Monitoring Based on EEMD

For the non-stationary characteristics of acoustic emission signals in face milling process,a new approach based on ensemble empirical mode decomposition(EEMD) and IMF energy distribution was proposed to achieve the detection and identification of tool breakage in milling process.First,EEMD was used on the original signal to extract intrinsic mode functions(IMFs),and then IMFs energy distribution was calculated to obtain the feature vector and a mathematical model was established to express the relationship between the feature vector and cutter conditions.Extensive experiments were performed to confirm the effectiveness and robustness of the detective method for steady milling and variable cutting parameters.The results showed that this method could accurately and stably identify the tool breakage.