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Texture-Driven Image Clustering in Laser Powder Bed Fusion

Groeger, Alexander H.
http://rave.ohiolink.edu/etdc/view?acc_num=wright1640680918896769

Abstract Details

2021, Master of Science (MS), Wright State University, Computer Science.
The additive manufacturing (AM) field is striving to identify anomalies in laser powder bed fusion (LPBF) using multi-sensor in-process monitoring paired with machine learning (ML). In-process monitoring can reveal the presence of anomalies but creating a ML classifier requires labeled data. The present work approaches this problem by printing hundreds of Inconel-718 coupons with different processing parameters to capture a wide range of process monitoring imagery with multiple sensor types. Afterwards, the process monitoring images are encoded into feature vectors and clustered to isolate groups in each sensor modality. Four texture representations were learned by training two convolutional neural network texture classifiers on two general texture datasets for clustering comparison. The results demonstrate unsupervised texture-driven clustering can isolate roughness categories and process anomalies in each sensor modality. These groups can be labeled by a field expert and potentially be used for defect characterization in process monitoring.
Tanvi Banerjee, Ph.D. (Advisor)
Thomas Wischgoll, Ph.D. (Committee Member)
John Middendorf, Ph.D. (Committee Member)
275 p.
Computer Science; Materials Science
lpbf; additive manufacturing; unsupervised; machine learning; deep learning; texture; embedding; clustering; insitu; monitoring; recoat; tomography; infrared; spatter; anomaly

Recommended Citations

Citations

  • Groeger, A. H. (2021). Texture-Driven Image Clustering in Laser Powder Bed Fusion [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1640680918896769

    APA Style (7th edition)

  • Groeger, Alexander. Texture-Driven Image Clustering in Laser Powder Bed Fusion. 2021. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1640680918896769.

    MLA Style (8th edition)

  • Groeger, Alexander. "Texture-Driven Image Clustering in Laser Powder Bed Fusion." Master's thesis, Wright State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright1640680918896769

    Chicago Manual of Style (17th edition)

wright1640680918896769
169
© 2021, some rights reserved.Creative Commons License Texture-Driven Image Clustering in Laser Powder Bed Fusion by Alexander H. Groeger is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Wright State University and OhioLINK.