Analytische Chemie
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- 2023 (1)
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- Englisch (1)
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- In-situ monitoring (1)
- Laser powder bed fusion (1)
- Machine Learning (1)
- Porosity (1)
- Thermography (1)
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In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.