About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
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| Symposium
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Additive Manufacturing: Advanced Characterization With Synchrotron, Neutron, and In Situ Laboratory-scale Techniques IV
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| Presentation Title |
Context information to enable localized acoustic monitoring of laser powder bed fusion |
| Author(s) |
Suraj Khan, Konstantinos Rousou, Shivam Shukla, Rik Vaerenberg, Ming Wu, Elke Deckers, Konstantinos Gryllias, Mathias Verbeke, Peter Karsmakers, Bey Vrancken |
| On-Site Speaker (Planned) |
Bey Vrancken |
| Abstract Scope |
The AM community has recently turned to acoustic sensing to complement visual monitoring techniques. This presents challenges dealing with background noise and complex signal interpretation, with solutions often reverting to black box machine learning models. As useful information is expected in high frequency ranges, high sampling rates for the acoustic sensors are required, but since the signals are non-stationary a time-frequency representation using e.g. the short-time Fourier transform is appropriate. Consequently, short signal patterns linked to defects might be difficult to discover. As a result, acoustic monitoring has largely been used on a layer level. This work utilizes three microphones, a structure-borne acoustic emission sensor, and high frequency transfer path simulations to capture the effect of microphone and part positioning, and directional scanning effects. It provides contextual information that is essential for advancing acoustic monitoring from the layer level to individual defect detection.
Supported by Flanders Make via 'MuSIC_SBO' project. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Process Technology, Other |