Related Experiment Video
Updated: May 28, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
Published on: May 15, 2017
Acoustic Source Localisation of Crack Initiation During Laser-Based DED: Experimental Validation and Challenges
Md Jonaet Ansari1,2, Elias J G Arcondoulis3, Anthony Roccisano1,2
1Future Industries Institute, Adelaide University, Mawson Lakes, SA 5095, Australia.
Abstract:
This study evaluates the feasibility of airborne acoustic source localisation (ASL) for in situ crack localisation in industrial laser-based directed energy deposition (DED-LB/M) fabricated structures. A four-microphone array combined with a Generalised Cross-Correlation with Phase Transform (GCC-PHAT) algorithm was used to estimate crack positions from time differences of arrival (TDOAs) extracted from raw acoustic emissions during multi-layer single-track fabrication. Prior to experimentation, the microphone array geometry was numerically optimised under industrial placement constraints by introducing controlled TDOA perturbations and minimising three-dimensional localisation uncertainty using alpha-shape volume analysis. Experimental validation was performed on six-layer single-track structures, with estimated crack positions compared against post-process microscopic measurements. Localisation errors ranged from 12 to 68 mm in the X-direction, 0.7-32 mm in the Y-direction, and 5-100 mm in the Z-direction. While horizontal localisation demonstrated centimetre-scale accuracy for most cracks, depth estimation exhibited greater variability. The results confirm that airborne ASL can provide meaningful spatial information regarding crack formation during DED-LB/M. However, localisation performance remains sensitive to TDOA estimation accuracy, microphone array constraints, and the complex acoustic environment inherent to the process. This work demonstrates the industrial feasibility of ASL for in situ crack investigation while highlighting the need for further advancements in array design and signal processing to achieve robust three-dimensional defect localisation in additive manufacturing systems.

