[3C2] Laser shock peening with acoustic emission in-situ monitoring for quality control
J Griffin¹, P Shukla², R Qin³ and P Butler Smith²
¹Coventry University, UK
²The Manufacturing Technology Centre, UK
³University of Edinburgh, UK
Laser shock peening (LSP) is a surface strengthening technology that imparts beneficial compressive residual stress and hardening depths on metal surfaces, improving fatigue resistance. Its principle involves using high-power laser pulses to generate plasma, confined by a transparent overlay, which produces shock waves that induce plastic deformation and residual compressive stress in the material. While LSP offers significant technical advantages and is valuable across various industries such as aerospace, defence and manufacturing, ensuring consistent surface quality is challenging due to process variability and complexity. Traditional surface quality inspection methods such as X-ray diffraction and the drilling method are offline, destructive and cannot provide real-time feedback, making them cumbersome for industrial applications. This necessitates the development of reliable, real-time quality assessment techniques. This paper posits a comparison between different types of LSP system, specifically considering potential distinctions between conventional industrial set-ups and potentially more accessible or ‘affordable’ systems. A key parameter noted in varying LSP experiments is laser pulse duration, with typical ‘industrial’ systems often utilising short pulse durations (tens of nanoseconds). Conversely, some experimental set-ups, potentially representing different system configurations, have been observed using higher pulse durations, such as 51 ns. This study explores how such differences in pulse duration, potentially characteristic of different system types, influence the fundamental LSP process, including plasma generation, shock wave characteristics and resulting material properties such as residual stress and hardness. This paper will discuss the implications for achieving the desired surface quality and the effectiveness of different monitoring techniques, such as acoustic emission (AE), for online quality assessment across these varying system configurations.
