Towards Defect Detection in Metal SLM Parts Using Modal Analysis "Fingerprinting"

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Date

2017

Authors

Urban, James
Capps, Nick
West, Brian
Hartwig, Troy
Brown, Ben
Landers, Robert
Bristow, Douglas
Kinzel, Edward

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University of Texas at Austin

Abstract

The validation of Additively Manufactured (AM) materials is a difficult and expensive process because the local engineering properties are a function of the thermal history. The thermal history varies with the process parameters, as well as the part geometry. This paper presents a case study using modal testing to identify defects in realistic AM parts. A setup consisting of a Scanning Laser Doppler Vibrometer (LDV) was used to identify the resonant frequencies for several geometrically identical parts on a build plate. Parts with suboptimal process parameters from purposely varying the process parameters, are identified by a shift in the mode peak frequency. Results from this study are compared to Finite Element Analysis (FEM) models and generalized for identifying defects in parts created with AM on the basis vibration/modal “fingerprinting.”

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