Optimized analytical approach for the detection of process-induced defects using acoustic emission during directed energy deposition process

Abstract

Directed energy deposition (DED), an advanced additive manufacturing (AM) technique, facilitates the production of complex metallic and metal matrix composite structures. The DED process has continuously improved and offers numerous advantages for depositing high-quality coatings with excellent wear and corrosion resistance onto metallic surfaces. The dynamic nature of the process, however, introduces a significant risk of process-induced defects in manufactured parts. This study presents an optimized analytical approach using acoustic emission (AE) based defect detection technique to identify and quantify process-induced cracks during the DED process. The developed signal processing technique enabled the identification of actual AE events associated with cracking, distinguishing them from other disturbances. Experimental validation was conducted using manufactured parts that were longitudinally sectioned to determine the relationship of the crack location with the recorded acoustic signal. The demonstrated correlation of acoustic signatures with cracking illustrates the robustness of the AE technique to identify the process-induced cracking for quality assurance during the DED process.