Advances and Perspectives in Using Medical Informatics for Steering Surgical Robots in Welding and Training of Welders Applying Long-Distance Communication Links

Main Article Content

Zbigniew Prusak
Ryszard Tadeusiewicz
Ryszard Jastrzębski
Ilona Jastrzębska

Abstract




This paper discusses various challenges in remote welding with a surgical robot equipped with a digital camera used to observe the welding zone, in particular the difficulty in detecting the boundaries of the weld pool. The difference in the processing of the real image by the human brain is discussed in comparison with the image in the form of a film from a digital camera. In addition to the need of performing the second derivative of the image in real-time, three models of human recognition of an image were discussed, one of which was already studied by researchers from Cambridge, UK. The concept of melting the base material by bending the weld pool with the pressure of non-ionized arc gases and the American implementation of the measurement of the third dimension of the weld pool and determining the weld penetration by electronics of the welding machine are discussed. Desired movement trajectories of the electrode tip based on the physics of the welding arc and welding technology are presented along with difficulties in teaching the movements to welding trainees. Basics of the neural model of the brain with the vector model of artificial intelligence are also presented.




Downloads

Download data is not yet available.

Article Details

How to Cite
[1]
Z. Prusak, R. Tadeusiewicz, R. Jastrzębski, and I. Jastrzębska, “Advances and Perspectives in Using Medical Informatics for Steering Surgical Robots in Welding and Training of Welders Applying Long-Distance Communication Links”, Weld. Tech. Rev., vol. 92, no. 5, pp. 37–49, Jun. 2020.
Section
Review

References

Dobrowolski Z., Tadeusiewicz R., Robotyka Urologiczna. Kraków, Poland, Lettra Graphic Publ., 2014.

Paton B.E., Krivtsun W.I., Marynsky G.S., Chernets I.Y., Khudetsky Y.N., Lankin S.E., et al., Zgrzewanie oraz obróbka termiczna żywych tkanek prądem o podwyższonej częstotliwości. Biuletyn Instytutu Spawalnictwa, 2014,(5), 92101.

Tadeusiewicz R., Jastrzębska I., Jastrzębski R., Możliwości stworzenia maski spawalniczej z komputerowym przetwarzaniem przestrzennego obrazu zamiast filtrów spawalniczych. Welding Technology Review, 2016, Vol. 88(1), 1722. https://doi.org/10.26628/ps.v88i1.558

Fabijańska A., Algorithms of image quality improvement in high-temperature measurements of physico-chemical properties of selected metals and their alloys. Ph.D. Diss. Łódź, Łódź University of Technology, 2007.

Fabijańska A., A survey of subpixel edge detection methods for images of heat-emitting metal specimens. International Journal of Applied Mathematics and Computer Science, 2012, 695710. https://doi.org/10.2478/v10006-012-0052-3

Łaski P.S., Pietrala D., Delta robot with pneumatic muscles for medical applications. Projektowanie i Konstrukcje Inżynierskie, 2019, Vol. 139(4), 3641.

Jastrzębski R., Control of MIG/MAG welding machines. Welding International, 2014, Vol. 29(16), 454456 https://doi.org/10.1080/09507116.2014.937592

Chmielewski T., Siwek P., Chmielewski M., Piątkowska A., Grabias A., Golański D., Structure and selected properties of arc sprayed coatings containing in-situ fabricated Fe-Al intermetallic phases. Metals, 2018, Vol. 8(12), 1059. https://doi.org/10.3390/met8121059

Wang Z., Zhang Y.M., Wu L., Measurement and estimation of weld pool surface depth and weld penetration in pulsed gas metal arc welding. Welding Journal (Miami, Fla), 2010, Vol. 89, 117126.

Lucas W., Bertaso D., Melton G., Smith J., Balfour C., Real-time vision-based control of weld pool size. Welding International, 2012, Vol. 26(4), 243250. https://doi.org/10.1080/09507116.2011.581336

Gontarz G., Golański D., Chmielewski T., Properties of Fe-Al Type Intermetallic Layers Produced by AC TIG Method. Advances in Materials Sciences, 2013, Vol. 13(3), 516. https://doi.org/10.2478/adms-2013-0007

Sukamu M., Tsuboi R., Kubo K., Asai S., Development of welders training support system with Visual Sensors.In: IIW document or XII-1813-04, Proceedings of IIW Conference, Osaka, Japan, 2004. p. 103108.

Yamamoto K., Tanaka M., Tashiro S., Nakata K., Yamazaki K., Yamamoto E., et al., Metal vapour behaviour in thermal plasma of gas tungsten arcs during welding. Science and Technology of Welding and Joining, 2008, Vol. 13(6), 566-572. https://doi.org/10.1179/174329308X319235

Olsen H.N., Thermal and electrical properties of an argon plasma. The Physics of Fluids, 1959, Vol. 2(6), 61423.

Jastrzębska I., Hercynite solid solutions synthesis, properties and applications. Ph.D. Diss. Kraków, AGH University of Science and Technology, 2017.

Lindsay P.H., Norman D.A., Human information processing. An introduction to psychology. New York, Academic Press, 1972.

Shabalin L.I., Ultra-High Temperature Materials II: Refractory Carbides I (Ta, Hf, Nb and Zr Carbides).Springer, 2019.