Obrabotka Metallov 2026 Vol. 28 No. 3

OBRABOTKAMETALLOV Vol. 28 No. 3 2026 165 EQUIPMENT. INSTRUMENTS 28. Zakovorotny V.L., Gvindjiliya V.E. Vliyanie vibratsii na traektorii formoobrazuyushchikh dvizhenii instrumenta pri tochenii [The infl uence of the vibration on the tool shape-generating trajectories when turning]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2019, vol. 21, no. 3, pp. 42–58. DOI: 10.17212/1994-6309-2019-21.3-42-58. (In Russian) 29. ZakovorotnyV.L., Gvindjiliya V.E. Dynamic infl uence of spindle wobble in a lathe on the workpiece geometry. Russian Engineering Research, 2018, vol. 38 (9), pp. 723–725. DOI: 10.3103/S1068798X18090307. 30. Zakovorotny V.L., Gvindjiliya V.E. Zavisimost’ iznashivaniya instrumenta i parametrov kachestva formiruemoi rezaniem poverkhnosti ot dinamicheskikh kharakteristik [The dependence of tool wear and quality parameters of the surface being cut on dynamic characteristics]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2019, vol. 21, no. 4, pp. 31–46. DOI: 10.17212/1994-63092019-21.4-31-46. (In Russian). 31. Dornfeld D., Pan S. Determination of chip formation states using the method of linear discriminant functions with acoustic emission. Proceedings of the 13th North American Manufacturing Research Conference, Berkeley, California, USA, May 19–22, 1985, pp. 299–303. 32. Banda T., Farid A.A., Li C., Jauw V.L., Lim C.S. Application of machine vision for tool condition monitoring and tool performance optimization – a review. The International Journal of Advanced Manufacturing Technology, 2022, vol. 121 (11–12), pp. 7057–7086. DOI: 10.1007/s00170-022-09696-x. 33. Munaro R., Attanasio A., Del Prete A. Tool wear monitoring with artifi cial intelligence methods. Journal of Manufacturing and Materials Processing, 2023, vol. 7 (4), p. 129. DOI: 10.3390/jmmp7040129. 34. Zhu K., Yu X. The monitoring of micro milling tool wear condition by wear area estimation. Mechanical Systems and Signal Processing, 2017, vol. 93, pp. 80–91. DOI: 10.1016/j.ymssp.2017.02.004. 35. Kozochkin M.P., Sabirov F.S., Molodtcov V.V. Diagnostika sostoyaniya stankov po vibratsionnym kharakteristikam [Diagnostics of the state of machines by vibration characteristics]. Materials. Technologies. Design, 2020, vol. 2, no. 1 (2), pp. 69–77. (In Russian). 36. Zakovorotny V.L., Ladnik I.V., Dhande S.G. A method for characterization of machine-tools dynamic parameters for diagnostic purposes. Journal of Materials Processing Technology, 1995, vol. 53 (3–4), pp. 588–600. DOI: 10.1016/0924-0136(95)01786-9. 37. RyzhkinA.A. Sinergetika iznashivaniya instrumental’nykh materialov pri lezviinoi obrabotke [Synergetics of tool wear in cutting edge treatment]. Rostov-on-Don, Don State Technical University Publ., 2019. 289 p. ISBN 9785-7890-1669-5. 38. Starkov V.K. Fizika i optimizatsiya rezaniya materialov [Physics and optimization of cutting of materials]. Moscow, Mashinostroenie Publ., 2009. 640 p. 39. Makarov A.D. Optimizatsiya protsessov rezaniya [Optimization of cutting processes]. Moscow, Mashinostroenie Publ., 1976. 278 p. 40. Kozhevnikov D.V., Kirsanov S.V. Rezanie materialov [Material cutting]. Moscow, Innovatsionnoe mashinostroenie Publ., 2022. 304 p. 41. TavstyukA.A., LyutovA.G., Kourov G.N. Primenenie udel’nykh energeticheskikh parametrov pri optimizatsii i upravlenii protsessom rezaniya [Application of specifi c energy parameters for optimization and control of the cutting process]. STIN: stanki, instrument = Russian Engineering Research, 2014, no. 2, pp. 29–34. (In Russian). 42. Migranov M.Sh. Issledovanie iznashivaniya instrumental’nykh materialov i pokrytii s pozitsii termodinamiki i samoorganizatsii [Study of wear of tool materials and coatings from the standpoint of thermodynamics and selforganization]. Izvestiya vysshikh uchebnykh zavedenii. Mashinostroenie = Proceedings of Higher Educational Institutions. Маchine Building, 2006, no. 11, pp. 65–70. (In Russian). 43. Zakovorotny V.L., Marchak M., Usikov I.V., Lukyanov A.D. Interrelation between tribosystem evolution and parameters of dynamic friction system. Journal of Friction and Wear, 1998, vol. 19 (6), pp. 54–64. 44. Zakovorotny V.L., Gvindjiliya V.E. Evolution of the dynamic cutting system with irreversible energy transformation in the machining zone. Russian Engineering Research, 2019, vol. 39 (5), pp. 423–433. DOI: 10.3103/ S1068798X19050204. 45. Zakovorotny V.L., Gvindzhiliya V.E. Bifurkatsii prityagivayushchikh mnozhestv deformatsionnykh smeshchenii rezhushchego instrumenta v khode evolyutsii svoistv protsessa obrabotki [Bifurcations of attracting sets of cutting tool deformation displacements at the evolution of treatment process properties]. Izvestiya vysshikh uchebnykh zavedenii. Prikladnaya nelineinaya dinamika = Izvestiya VUZ. Applied Nonlinear Dynamics, 2018, vol. 26, no. 5, pp. 20–38. DOI: 10.18500/0869-6632-2018-26-5-20-38. 46. Kabaldin Yu.G., Kuz’mishina A.M., Shatagin D.A., Anosov M.S. Neironno-setevoe modelirovanie protsessa iznashivaniya tverdosplavnogo instrumenta [Neural network modeling of the wear process of a carbide cutting tool].

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