  Melt pool (MP) temperature is one of the determining factors and key
signatures for the properties of printed components during metal additive
manufacturing (AM). The state-of-the art measurement systems are hindered by
both the equipment cost and the large-scale data acquisition and processing
demands. In this work, we introduce a novel coaxial high-speed single-camera
two-wavelength imaging pyrometer (STWIP) system as opposed to the typical
utilization of multiple cameras for measuring MP temperature profiles through a
laser powder bed fusion (LPBF) process. Developed on a commercial LPBF machine
(EOS M290), the STWIP system is demonstrated to be able to quantitatively
monitor MP temperature and variation for 50 layers at high framerates (> 30,000
fps) during a print of five standard fatigue specimens. High performance
computing is employed to analyze the acquired big data of MP images for
determining each MPs average temperature and 2D temperature profile. The MP
temperature evolution in the gage section of a fatigue specimen is also
examined at a temporal resolution of 1ms by evaluating the derived MP
temperatures of the printed samples first, middle and last layers. This paper
is first of its kind on monitoring MP temperature distribution and evolution at
such a large, detailed scale for longer durations in practical applications.
Future work includes MP registration and machine learning of MP-Part Property
relations.
