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Session: 07-01: NDE for Additive Manufacturing
Paper Number: 98061
98061 - Online Monitoring of Internal Surface Roughness of Additively Manufactured Parts
Additive manufacturing (AM) can create parts with internal features and channels. However, the as-printed surfaces are usually rough and prone to corrosion attacks and fatigue crack incubation. Therefore, surface finishing is needed in many applications. For internal channels, it is difficult to use conventional surface metrology techniques, such like stylus profilometer and optical microscope. In this work, we present a method to reconstruct the roughness information of internal surfaces of AM components by analyzing the spectrum of ultrasonic reflections. The attenuation caused by the scattering on the target surface and its dependency on frequency are used to reconstruct the root-mean-square roughness (Rq) quantitatively. Finite element simulations are conducted to demonstrate the method and to study the reconstruction errors due to the finite size of the ultrasonic probe. The method is then applied to monitor the surface roughness of the internal channels during the Abrasive Flow Machining (AFM) process. The finishing progress can be indicated by the reconstructed roughness value, which shows a clear and steady downward trend. Moreover, the polishing rate, which varies with the pressure in the AFM machine, has been captured by the developed technique as well. The experimental results demonstrates that such ultrasonic method may provide feedback controls in the polishing process.
Presenting Author: Zeqing Sun Nanyang Technological University
Online Monitoring of Internal Surface Roughness of Additively Manufactured Parts