Differentiation of materials and laser powder bed fusion processing regimes from airborne acoustic emission combined with machine learning-Reference-Cited by-同舟云学术

Differentiation of materials and laser powder bed fusion processing regimes from airborne acoustic emission combined with machine learning

Published:2022-02-25 Issue:2 Volume:17 Page:181-204
ISSN:1745-2759
Container-title:Virtual and Physical Prototyping
language:en
Short-container-title:Virtual and Physical Prototyping

Author:

Drissi-Daoudi Rita¹,Pandiyan Vigneashwara²^ORCID,Logé Roland¹^ORCID,Shevchik Sergey²^ORCID,Masinelli Giulio²^ORCID,Ghasemi-Tabasi Hossein¹^ORCID,Parrilli Annapaola³^ORCID,Wasmer Kilian²^ORCID

Affiliation:

1. Thermomechanical Metallurgy Laboratory – PX Group Chair, Ecole Polytechnique Fédérale de Lausanne (EPFL), Neuchâtel, Switzerland

2. Laboratory for Advanced Materials Processing (LAMP), Swiss Federal Laboratories for Materials Science and Technology (Empa), Thun, Switzerland

3. Centre for X-ray Analytics, Swiss Federal Laboratories for Materials Science and Technology (EMPA), Dübendorf, Switzerland

Funder

Strategic Focus Area Advanced Manufacturing (SFA-AM) programme

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Modeling and Simulation,Signal Processing

Link

https://www.tandfonline.com/doi/pdf/10.1080/17452759.2022.2028380

Reference73 articles.

1. Reducing porosity in AlSi10Mg parts processed by selective laser melting

2. Smoothing Periodograms from Time-Series with Continuous Spectra

3. Machine learning-based image processing for on-line defect recognition in additive manufacturing

4. Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum

5. Process monitoring and inspection systems in metal additive manufacturing: Status and applications

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