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Monitoring of Laser Powder Bed Fusion process by bridging dissimilar process maps using deep learning-based domain adaptation on acoustic emissions
Pandiyan, V., Wróbel, R., Richter, R. A., Leparoux, M., Leinenbach, C., & Shevchik, S. (2024). Monitoring of Laser Powder Bed Fusion process by bridging dissimilar process maps using deep learning-based domain adaptation on acoustic emissions. Additive Manufacturing, 80, 103974 (13 pp.). https://doi.org/10.1016/j.addma.2024.103974
Optimizing in-situ monitoring for laser powder bed fusion process: deciphering acoustic emission and sensor sensitivity with explainable machine learning
Pandiyan, V., Wróbel, R., Leinenbach, C., & Shevchik, S. (2023). Optimizing in-situ monitoring for laser powder bed fusion process: deciphering acoustic emission and sensor sensitivity with explainable machine learning. Journal of Materials Processing Technology, 321, 118144 (17 pp.). https://doi.org/10.1016/j.jmatprotec.2023.118144
Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring
Pandiyan, V., Wróbel, R., Richter, R. A., Leparoux, M., Leinenbach, C., & Shevchik, S. (2023). Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring. Materials and Design, 235, 112458 (15 pp.). https://doi.org/10.1016/j.matdes.2023.112458
Supervised deep learning for real-time quality monitoring of laser welding with X-ray radiographic guidance
Shevchik, S., Le-Quang, T., Meylan, B., Vakili Farahani, F., Olbinado, M. P., Rack, A., … Wasmer, K. (2020). Supervised deep learning for real-time quality monitoring of laser welding with X-ray radiographic guidance. Scientific Reports, 10, 3389 (12 pp.). https://doi.org/10.1038/s41598-020-60294-x
Deep learning for<em> in situ </em>and real-time quality monitoring in additive manufacturing using acoustic emission
Shevchik, S. A., Masinelli, G., Kenel, C., Leinenbach, C., & Wasmer, K. (2019). Deep learning for in situ and real-time quality monitoring in additive manufacturing using acoustic emission. IEEE Transactions on Industrial Informatics, 15(9), 5194-5203. https://doi.org/10.1109/TII.2019.2910524
Acoustic emission for in situ quality monitoring in additive manufacturing using spectral convolutional neural networks
Shevchik, S. A., Kenel, C., Leinenbach, C., & Wasmer, K. (2018). Acoustic emission for in situ quality monitoring in additive manufacturing using spectral convolutional neural networks. Additive Manufacturing, 21, 598-604. https://doi.org/10.1016/j.addma.2017.11.012
AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence
Wasmer, K., Le, T. Q., Meylan, B., Vakili-Farahani, F., Leinenbach, C., Olbinado, M. P., … Shevchik, S. A. (2018). AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence. Presented at the ESRF user meeting 2018. Grenoble, France.
In situ quality monitoring in am using acoustic emission: a machine learning approach
Wasmer, K., Kenel, C., Leinenbach, C., & Shevchik, S. A. (2017). In situ quality monitoring in am using acoustic emission: a machine learning approach (pp. 386-388). Presented at the Materials science and technology (MS&T17). https://doi.org/10.7449/2017/MST_2017_386_388