Tribological Behavior of Sheet Metal Forming Process Using Acoustic Emission Characteristics

In this study, acoustic emissions (AE) signal processing using wavelet packet transform technique was used to identify damage mechanisms during sheet metal forming simulation experiments. Current investigation was carried out based on decomposing the recorded AE signals into different wavelet levels. Following decomposition process, the energy distribution criteria were used to characterize dominant components, which are considered to be related to dominant damage mechanisms. Results revealed that the energy of AE signals was distributed dominantly on four components, which can be correlated by 3 specific damage mechanisms occurred during simulation experiments. After comparison with previous works, results were validated by surface observations in order to establish a meaningful relation between dominant wavelet components and surface damage mechanisms.