Automatic Classification of Laser Peening Quality Using Acoustic Signals

TL;DR

This paper introduces a low-cost acoustic signal analysis method for real-time, non-destructive classification of laser peening quality, enabling continuous in-line process monitoring and improved reliability.

Contribution

The study presents a novel acoustic-based approach for automatic, real-time classification of laser peening pulses, reducing reliance on destructive testing and subjective judgment.

Findings

Acoustic signals reliably distinguish defect-free from defective laser impacts.

The method enables real-time, non-destructive quality control.

Low-cost microphones suffice for accurate classification.

Abstract

Laser Shock Peening increases the fatigue life of metallic components by introducing beneficial compressive residual stresses. To achieve the desired effect, each individual laser pulse must be delivered correctly. Laser Shock Peening quality is typically verified by destructive and time-consuming residual stress measurements or by subjective operator judgement, which is non-objective and unsuitable for continuous in-line control. We propose a simple, low-cost and robust method based on the analysis of the acoustic response that automatically classifies individual laser pulses as defect-free or defective. We show that the acoustic response captured by a low-cost microphone carries sufficiently informative signatures to reliably distinguish correct from incorrect impacts and enables quality control at the level of single pulses. The method provides a non-destructive and objective route to real-time monitoring of Laser Shock Peening, with the potential to increase process reliability and support industrial deployment of this technology without the need for subsequent destructive measurements.