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25 April 2023 Developing XCT data sets for evaluation of automated flaw detection algorithms (Conference Presentation)
Felix Kim, Owen V. Hammer, Adam L. Pintar, John Henry J. Scott, Edward J. Garboczi
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Proceedings Volume PC12491, 8th International Workshop on Reliability of NDT/NDE; PC1249108 (2023) https://doi.org/10.1117/12.2657270
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States
Abstract
X-ray computed tomography (XCT) is a promising non-destructive evaluation technique for various advanced manufacturing industries including additive manufacturing (AM). In an AM part, different types of flaws such as lack-of-fusion pores, gas pores, keyhole pores, near-surface pores, and trapped powders can occur. An automated/assisted flaw detection algorithms are expected to be implemented for an automated analysis and inspection. Evaluation and qualification of the algorithm’s flaw capability is a critical aspect of NDT qualification. NIST is developing a computational framework to generate data sets for evaluation of detection algorithms based on realistic XCT simulation. In this presentation, we will describe our workflow to generate complex pore shapes and distribute them in realistic AM parts. Example application and evaluation results will be discussed using various evaluation metrics. Such data sets are expected to help evaluate reliability of detection algorithms.
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Felix Kim, Owen V. Hammer, Adam L. Pintar, John Henry J. Scott, and Edward J. Garboczi "Developing XCT data sets for evaluation of automated flaw detection algorithms (Conference Presentation)", Proc. SPIE PC12491, 8th International Workshop on Reliability of NDT/NDE, PC1249108 (25 April 2023); https://doi.org/10.1117/12.2657270
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KEYWORDS
Algorithm development
Detection and tracking algorithms
Additive manufacturing
Binary data
Nondestructive evaluation
Computer simulations
Inspection
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