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Acoustic emission and machine learning based classification of wear generated using a pin-on-disc tribometer equipped with a digital holographic microscope
Deshpande, P., Pandiyan, V., Meylan, B., & Wasmer, K. (2021). Acoustic emission and machine learning based classification of wear generated using a pin-on-disc tribometer equipped with a digital holographic microscope. Wear, 203622 (12 pp.). https://doi.org/10.1016/j.wear.2021.203622
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
Acoustic emission and machine learning for in situ monitoring of a gold-copper ore weakening by electric pulse
Meylan, B., Shevchik, S. A., Parvaz, D., Mosaddeghi, A., Simov, V., & Wasmer, K. (2021). Acoustic emission and machine learning for in situ monitoring of a gold-copper ore weakening by electric pulse. Journal of Cleaner Production, 280, 124348 (12 pp.). https://doi.org/10.1016/j.jclepro.2020.124348
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
Monitoring of friction-related failures using diffusion maps of acoustic time series
Shevchik, S. A., Zanoli, S., Saeidi, F., Meylan, B., Flück, G., & Wasmer, K. (2021). Monitoring of friction-related failures using diffusion maps of acoustic time series. Mechanical Systems and Signal Processing, 148, 107172 (14 pp.). https://doi.org/10.1016/j.ymssp.2020.107172
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
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
Nanosecond pulsed laser-processing of CVD diamond
Mouhamadali, F., Equis, S., Saeidi, F., Best, J. P., Cantoni, M., Hoffmann, P., & Wasmer, K. (2020). Nanosecond pulsed laser-processing of CVD diamond. Optics and Lasers in Engineering, 126, 105917 (12 pp.). https://doi.org/10.1016/j.optlaseng.2019.105917
Analysis of time, frequency and time-frequency domain features from acoustic emissions during laser powder-bed fusion process
Pandiyan, V., Drissi-Daoudi, R., Shevchik, S., Masinelli, G., Logé, R., & Wasmer, K. (2020). Analysis of time, frequency and time-frequency domain features from acoustic emissions during laser powder-bed fusion process. In M. Schmidt, F. Vollertsen, & E. Govekar (Eds.), Procedia CIRP: Vol. 94. 11th CIRP conference on photonic technologies [LANE 2020] (pp. 392-397). https://doi.org/10.1016/j.procir.2020.09.152
Modelling and monitoring of abrasive finishing processes using artificial intelligence techniques: a review
Pandiyan, V., Shevchik, S., Wasmer, K., Castagne, S., & Tjahjowidodo, T. (2020). Modelling and monitoring of abrasive finishing processes using artificial intelligence techniques: a review. Journal of Manufacturing Processes, 57, 114-135. https://doi.org/10.1016/j.jmapro.2020.06.013
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
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
Damping of post-impact vibrations
Muster, M., Hameed, A., Wood, D., Appleby-Thomas, G., & Wasmer, K. (2019). Damping of post-impact vibrations. Applied Acoustics, 156, 427-433. https://doi.org/10.1016/j.apacoust.2019.07.040
Push-out force and impulse measurement of seven types of small arms ammunition with three different surface states
Muster, M., Hameed, A., Wood, D., & Wasmer, K. (2019). Push-out force and impulse measurement of seven types of small arms ammunition with three different surface states. AIP Advances, 9(11), 115016 (9 pp.). https://doi.org/10.1063/1.5128440
Characterization of ablated bone and muscle for long-pulsed laser ablation in dry and wet conditions
Nguendon Kenhagho, H., Shevchik, S., Saeidi, F., Faivre, N., Meylan, B., Rauter, G., … Zam, A. (2019). Characterization of ablated bone and muscle for long-pulsed laser ablation in dry and wet conditions. Materials, 12(8), 1338 (16 pp.). https://doi.org/10.3390/ma12081338
3D reconstruction of cracks propagation in mechanical workpieces analyzing non-stationary acoustic mixtures
Shevchik, S. A., Meylan, B., Violakis, G., & Wasmer, K. (2019). 3D reconstruction of cracks propagation in mechanical workpieces analyzing non-stationary acoustic mixtures. Mechanical Systems and Signal Processing, 119, 55-64. https://doi.org/10.1016/j.ymssp.2018.09.022
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
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
Nanoindentation deformation and cracking in sapphire
Trabadelo, V., Pathak, S., Saeidi, F., Parlinska-Wojtan, M., & Wasmer, K. (2019). Nanoindentation deformation and cracking in sapphire. Ceramics International, 45(8), 9835-9845. https://doi.org/10.1016/j.ceramint.2019.02.022
 

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