11 May 2016 Multiple sensor detection of process phenomena in laser powder bed fusion
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Abstract
Laser powder bed fusion (LPBF) is an additive manufacturing (AM) process in which a high power laser melts metal powder layers into complex, three-dimensional shapes. LPBF parts are known to exhibit relatively high residual stresses, anisotropic microstructure, and a variety of defects. To mitigate these issues, in-situ measurements of the melt-pool phenomena may illustrate relationships between part quality and process signatures. However, phenomena such as spatter, plume formation, laser modulation, and melt-pool oscillations may require data acquisition rates exceeding 10 kHz. This hinders use of relatively data-intensive, streaming imaging sensors in a real-time monitoring and feedback control system. Single-point sensors such as photodiodes provide the temporal bandwidth to capture process signatures, while providing little spatial information.

This paper presents results from experiments conducted on a commercial LPBF machine which incorporated synchronized, in-situ acquisition of a thermal camera, high-speed visible camera, photodiode, and laser modulation signal during fabrication of a nickel alloy 625 AM part with an overhang geometry. Data from the thermal camera provides temperature information, the visible camera provides observation of spatter, and the photodiode signal provides high temporal bandwidth relative brightness stemming from the melt pool region. In addition, joint-time frequency analysis (JTFA) was performed on the photodiode signal. JTFA results indicate what digital filtering and signal processing are required to highlight particular signatures. Image fusion of the synchronized data obtained over multiple build layers allows visual comparison between the photodiode signal and relating phenomena observed in the imaging detectors.
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Brandon Lane, Eric Whitenton, Shawn Moylan, "Multiple sensor detection of process phenomena in laser powder bed fusion", Proc. SPIE 9861, Thermosense: Thermal Infrared Applications XXXVIII, 986104 (11 May 2016); doi: 10.1117/12.2224390; https://doi.org/10.1117/12.2224390
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