Acoustic laser triangulation and tagging for additive manufacturing process monitoring

Research output: Contribution to journalArticlepeer-review

Abstract

Challenges in assessing build quality is one the significant hurdles that limits widespread adoption of additive manufacturing (AM) for critical applications. Collecting acoustic process emissions is a compelling yet cost effective strategy for monitoring AM processes. However, several technical challenges need to be overcome initially in order to fully leverage the information content of the captured acoustic emissions and to potentially correlate specific acoustic sensor footprints to the process anomalies that can often associated with build defects and a reduction in part quality or performance. This paper aims to address some of these challenges, provide potential technical solutions, and offer guidelines in order to enable process monitoring of powder bed fusion (PBF) AM processes using acoustic sensors in the near future. Experimental data collected during a PBF-AM process is utilized to characterize the acoustic footprint of the interaction between the laser and the powder bed. Differences between active and inactive periods of the laser are highlighted in the frequency domain. A significant initial acoustic transient was observed, associated with laser turn-on. Automated data alignment strategies are explored that aim to compensate for the time of flight delay as a function of location on the build plate. Proper data alignment may be utilized to triangulate laser location using an array of microphones, which could open up potential for use on multi-laser PBF-AM systems or systems in which the laser position data is not available to the end-user. Triangulation is demonstrated using experimental data.

Original languageEnglish (US)
Pages (from-to)3233-3245
Number of pages13
JournalInternational Journal of Advanced Manufacturing Technology
Volume129
Issue number7-8
DOIs
StatePublished - Dec 2023

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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