التفاصيل البيبلوغرافية
| العنوان: |
Monitoring via Machine‐Learning: Machine‐Learning‐Based Monitoring of Laser Powder Bed Fusion (Adv. Mater. Technol. 12/2018). |
| المؤلفون: |
Yuan, Bodi, Guss, Gabriel M., Wilson, Aaron C., Hau‐Riege, Stefan P., DePond, Phillip J., McMains, Sara, Matthews, Manyalibo J., Giera, Brian |
| المصدر: |
Advanced Materials Technologies; Dec2018, Vol. 3 Issue 12, pN.PAG-N.PAG, 1p |
| مصطلحات موضوعية: |
LASERS, NEURAL circuitry, SPEED, VIDEOS, STANDARD deviations |
| مستخلص: |
A procedure to label Laser Powder Bed Fusion video data and leverage it to train a convolutional neural network is demonstrated in article number 1800136, by Bodi Yuan, Brian Giera, and co‐workers. Testing the neural network reveals it can predict track continuity and the average and standard deviations of track width from high speed video alone, reducing the need for post‐build quality assessment. [ABSTRACT FROM AUTHOR] |
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