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Acoustic Emission for <i>in situ</i> monitoring of laser processing
Shevchik, S., Le, Q. T., Meylan, B., & Wasmer, K. (2018). Acoustic Emission for in situ monitoring of laser processing. In Conference proceedings Ewgae 2018 (p. (9 pp.). CETIM.
When AE (acoustic emission) meets AI (artificial intelligence) II
Wasmer, K., Saeidi, F., Meylan, B., Le, Q. T., & Shevchik, S. A. (2018). When AE (acoustic emission) meets AI (artificial intelligence) II. In Conference proceedings Ewgae 2018 (p. (12 pp.). CETIM.
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.
Why is in situ quality control of laser keyhole welding a real challenge?
Le-Quang, T., Shevchik, S. A., Meylan, B., Vakili-Farahani, F., Olbinado, M. P., Rack, A., & Wasmer, K. (2018). Why is in situ quality control of laser keyhole welding a real challenge? In M. Schmidt, F. Vollertsen, & G. Dearden (Eds.), Procedia CIRP: Vol. 74. 10th CIRP conference on photonic technologies [LANE 2018] (pp. 649-653). https://doi.org/10.1016/j.procir.2018.08.055
Laser processing quality monitoring by combining acoustic emission and machine learning: a high-speed X-ray imaging approach
Wasmer, K., Le-Quang, T., Meylan, B., Vakili-Farahani, F., Olbinado, M. P., Rack, A., & Shevchik, S. A. (2018). Laser processing quality monitoring by combining acoustic emission and machine learning: a high-speed X-ray imaging approach. In M. Schmidt, F. Vollertsen, & G. Dearden (Eds.), Procedia CIRP: Vol. 74. 10th CIRP conference on photonic technologies [LANE 2018] (pp. 654-658). https://doi.org/10.1016/j.procir.2018.08.054
Piezo acoustic versus opto-acoustic sensors in laser processing
Wasmer, K., Le-Quang, T., Shevchik, S. A., & Violakis, G. (2019). Piezo acoustic versus opto-acoustic sensors in laser processing. In NDT.net (p. (8 pp.).
Laser welding quality monitoring via graph support vector machine with data adaptive kernel
Shevchik, S. A., Le-Quang, T., Farahani, F. V., Faivre, N., Meylan, B., Zanoli, S., & Wasmer, K. (2019). Laser welding quality monitoring via graph support vector machine with data adaptive kernel. IEEE Access, 7, 93108-93122. https://doi.org/10.1109/ACCESS.2019.2927661
Sensitivity analysis of acoustic emission detection using fiber bragg gratings with different optical fiber diameters
Violakis, G., Le-Quang, T., Shevchik, S. A., & Wasmer, K. (2020). Sensitivity analysis of acoustic emission detection using fiber bragg gratings with different optical fiber diameters. Sensors, 20(22), 6511 (11 pp.). https://doi.org/10.3390/s20226511
Re-solidification dynamics and microstructural analysis of laser welded aluminium
Meylan, B., Le-Quang, T., Olbinado, M. P., Rack, A., Shevchik, S. A., & Wasmer, K. (2020). Re-solidification dynamics and microstructural analysis of laser welded aluminium. International Journal of Materials Research, 111(1), 17-22. https://doi.org/10.3139/146.111838
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
Adaptive laser welding control: a reinforcement learning approach
Masinelli, G., Le-Quang, T., Zanoli, S., Wasmer, K., & Shevchik, S. A. (2020). Adaptive laser welding control: a reinforcement learning approach. IEEE Access, 8, 103803-103814. https://doi.org/10.1109/ACCESS.2020.2998052
Investigations of surface defects during laser polishing of tool steel
Meylan, B., Calderon, I., Tri Le, Q., & Wasmer, K. (2020). Investigations of surface defects during laser polishing of tool steel. In M. Schmidt, F. Vollertsen, & E. Govekar (Eds.), Procedia CIRP: Vol. 94. 11th CIRP conference on photonic technologies [LANE 2020] (pp. 942-946). https://doi.org/10.1016/j.procir.2020.09.092
Machine learning monitoring for laser osteotomy
Shevchik, S., Nguendon Kenhagho, H., Le-Quang, T., Faivre, N., Meylan, B., Guzman, R., … Wasmer, K. (2021). Machine learning monitoring for laser osteotomy. Journal of Biophotonics, 14(4), e202000352 (11 pp.). https://doi.org/10.1002/jbio.202000352
Artificial intelligence for monitoring and control of metal additive manufacturing
Masinelli, G., Shevchik, S. A., Pandiyan, V., Quang-Le, T., & Wasmer, K. (2021). Artificial intelligence for monitoring and control of metal additive manufacturing. In M. Meboldt & C. Klahn (Eds.), Industrializing additive manufacturing. Proceedings of AMPA2020 (pp. 205-220). https://doi.org/10.1007/978-3-030-54334-1_15
Energy-efficient laser welding with beam oscillating technique - a parametric study
Le-Quang, T., Faivre, N., Vakili-Farahani, F., & Wasmer, K. (2021). Energy-efficient laser welding with beam oscillating technique - a parametric study. Journal of Cleaner Production, 313, 127796 (11 pp.). https://doi.org/10.1016/j.jclepro.2021.127796
Semi-supervised monitoring of laser powder bed fusion process based on acoustic emissions
Pandiyan, V., Drissi-Daoudi, R., Shevchik, S., Masinelli, G., Le-Quang, T., Logé, R., & Wasmer, K. (2021). Semi-supervised monitoring of laser powder bed fusion process based on acoustic emissions. Virtual and Physical Prototyping, 16(4), 481-497. https://doi.org/10.1080/17452759.2021.1966166
Smart closed-loop control of laser welding using reinforcement learning
Le Quang, T., Meylan, B., Masinelli, G., Saeidi, F., Shevchik, S. A., Farahani, F. V., & Wasmer, K. (2022). Smart closed-loop control of laser welding using reinforcement learning. In M. Schmidt, F. Vollertsen, & B. M. Colosimo (Eds.), Procedia CIRP: Vol. 111. 12th CIRP conference on photonic technologies [LANE 2022] (pp. 479-483). https://doi.org/10.1016/j.procir.2022.08.074
Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and <em>operando</em> X-ray radiography guidance
Pandiyan, V., Masinelli, G., Claire, N., Le-Quang, T., Hamidi-Nasab, M., de Formanoir, C., … Wasmer, K. (2022). Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and operando X-ray radiography guidance. Additive Manufacturing, 58, 103007 (15pp.). https://doi.org/10.1016/j.addma.2022.103007
Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process
Pandiyan, V., Drissi-Daoudi, R., Shevchik, S., Masinelli, G., Le-Quang, T., Logé, R., & Wasmer, K. (2022). Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process. Journal of Materials Processing Technology, 303, 117531 (14 pp.). https://doi.org/10.1016/j.jmatprotec.2022.117531
In situ quality monitoring in direct energy deposition process using co-axial process zone imaging and deep contrastive learning
Pandiyan, V., Cui, D., Le-Quang, T., Deshpande, P., Wasmer, K., & Shevchik, S. (2022). In situ quality monitoring in direct energy deposition process using co-axial process zone imaging and deep contrastive learning. Journal of Manufacturing Processes, 81, 1064-1075. https://doi.org/10.1016/j.jmapro.2022.07.033