Online Evaluation of Surface Hardness for Aluminum Alloy in LSP Using Modal Acoustic Emission

This article researches the online evaluation method of surface integrity for aluminum alloy in laser shock peening (LSP) based on multiple-sources modal acoustic emission (MAE). First, a new comprehensive index e.g., sub-surface microhardening rate (SHR) for 7075 aluminum alloy in LSP was constructed to characterize both the impact depth (
$150 \mu \text{m}$
) and its hardening rate. Then, a good linear and positive correlation between the SHR of 7075 Al alloy and the AE features in time domain and frequency domain was revealed based on the offline quantitative characterization of SHR and the antisymmetric zero (A0) mode separated from AE signal. In addition, the A0 mode-based Mel frequency cepstrum coefficient (AMFCC) was proposed to deeply extract the time-frequency features of MAE-A0 mode signal. Finally, the SHR classification model based on AMFCC and gradient boosting decision tree for 7075 Al alloy in LSP process was established and was carefully validated using the experimental data. The test results showed the highest mean accuracy of 96.24% after the thorough comparison with other tree models and the traditional cepstrum methods. More importantly, deep analysis about the feature importance and their physical interpretation has been conducted from the perspective of non-linear effect inside the LSP material caused by dislocation multiplication as well as the increasing harmonic component of the MAE-A0 signal. This article can provide certain guidance for the development of LSP quality monitoring technology.