Shared New Acoustic Leakage Data Set
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Updated
Dec 9, 2021 - Python
Shared New Acoustic Leakage Data Set
In Situ Quality Monitoring in Direct Energy Deposition Process using Co-axial Process Zone Imaging and Deep Contrastive Learning
Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and operando X-ray radiography guidance
Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process
Semi-supervised monitoring of laser powder bed fusion process based on acoustic emissions
Repositry supporting two publications on LPBF process monitoring using acoustic emissions
Sensor selection for process monitoring based on deciphering acoustic emissions from different dynamics of the Laser Powder Bed Fusion process using Empirical Mode Decompositions and Interpretable Machine Learning
Self-Supervised Bayesian Representation Learning of Acoustic Emissions from Laser Powder Bed Fusion Process for In-situ Monitoring
Monitoring Of Laser Powder Bed Fusion Process By Bridging Dissimilar Process Maps Using Deep Learning-based Domain Adaptation on Acoustic Emissions
"The sound of typing: using Machine Learning to classify Keyboard Acoustic Emanations" 2024 bachelor thesis source code.
Open standard of feature extraction algorithms
Library to easily interface with Vallen Systeme WaveLine™ devices
read acoustic emission txt data files and generate initial summary and plot charts and graphs using matplotlib
Methods for the automated detection of acoustic multiplets and their hierarchical classification according to the similarity of their emission mechanisms
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