Tian, Wenmeng (Meg)
Date of Degree
Original embargo terms
Visible to MSU only for 6 months||forever||5/15/2021
Graduate Thesis - Open Access
Master of Science
Quality assurance has been one of the major challenges in laser-based additive manufacturing (AM) processes. This study proposes a novel process modeling methodology for layer-wise in-situ quality monitoring based on image series analysis. An image-based autoregressive (AR) model has been proposed based on the image registration function between consecutively observed thermal images. Image registration is used to extract melt pool location and orientation change between consecutive images, which contains sensing stability information. Subsequently, a Gaussian process model is used to characterize the spatial correlation within the error matrix. Finally, the extracted features from the aforementioned processes are jointly used for layer-wise quality monitoring. A case study of a thin wall fabrication by a Directed Laser Deposition (DLD) process is used to demonstrate the effectiveness of the proposed methodology.
Noroozi Esfahani, Mehrnaz, "Advanced in-situ layer-wise quality control for laser-based additive manufacturing using image sequence analysis" (2020). Theses and Dissertations MSU. 402.