ISSN (print) 1995-2732
ISSN (online) 2412-9003

 

download PDF

DOI: 10.18503/1995-2732-2023-21-3-51-61

Abstract

The paper presents the results of experimental studies conducted to determine the effect of the main technological parameters of reverse surface plastic deformation (SPD) on compressive residual stresses on the surface of parts. To implement the proposed method of finishing and hardening processing, a device has been developed providing a reverse circular movement of the working tool. Using the Barkhausen effect, we determined the value of compressive residual stresses on the surface of parts. Experimental studies have shown that the value of compressive residual stresses during reverse SPD varies from 210 to 345 MPa and depends on the main technological parameters of the process. A radial interference fit and reverse rotational velocity of the working tool have the greatest influence on compressive residual stresses among the main technological parameters of the reverse SPD. An increase in the radial interference fit, reverse rotational velocity of the working tool and a decrease in longitudinal feed leads to a very significant increase in compressive residual stresses on the surface of the part (σres ~ 342-345 MPa). It has been established that the difference between the experimental and calculated results does not exceed 20%. According to the experimental studies performed using the Microsoft Visual Studio 2012 computer program with the Python programming language, the optimal hardening modes were determined to ensure maximum compressive residual stresses on the surface of the part: longitudinal feed was 0.07-0.10 mm/rev; rotational velocity of the workpiece was 280-300 rpm; the radial interference fit was 0.25-0.28 mm; reverse rotational velocity of working tool was 250-300 double stroke/min; the initial angle of installation of the working tool was 90° and the angle of reverse rotation of the working tool was ±55° – ±60°.

Keywords

reverse surface plastic deformation, compressive residual stresses, two-radius roller, reverse rotational velocity, Barkhausen noise

For citation

Zaides S.A., Nguyen Huu Hai. Determination of Residual Stresses by Using Barkhausen Noise in the Reverse Surface Plastic Deformation. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2023, vol. 21, no. 3, pp. 51-61. https://doi.org/10.18503/1995-2732-2023-21-3-51-61

Semen A. Zaides – DrSc (Eng.), Professor, Irkutsk National Research Technical University, Irkutsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID: 0000-0001-9416-7749

Nguyen Huu Hai – postgraduate student, Irkutsk National Research Technical University, Irkutsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID: 0000-0001-7909-385Х

1. Odintsov L.G. Uprochnenie i otdelka detalei poverkhnostnym plasticheskim deformirovaniem [Hardening and finishing of parts by surface plastic deformation]. Moscow: Mashinostroenie, 1987, 328 p. (In Russ.)

2. Smelyansky V.M. Mekhanika uprochneniya detalei poverkhnostnym plasticheskim deformirovaniem [Mechanics of hardening of parts by surface plastic deformation]. Moscow: Mashinostroenie, 2002, 300 p. (In Russ.)

3. Butakov B.I., Shebanin V.S., Marchenko D.D., Artyukh A.V. Surface plastic deformation as a method for improving the quality of machine parts. Trudy GOSNITI [Proceedings of GOSNITI]. 2011;107(2):85-87. (In Russ.)

4. Blyumenshtein V.Yu., Makhalov M.S. Influence of modes on the formation of residual stresses in the surface layer during dimensional combined burnishing. Obrabotka metallov [Metal Working]. 2008;(2(39)):15-22. (In Russ.)

5. Prosvirkina E.A., Saushkin M.N. Research on the fields of residual stresses and plastic deformations during surface hardening of a cylindrical sample taking into account the organization of the surface plastic deformation process. Vestnik Samarskogo gosudarstvennogo tekhnicheskogo universiteta. Seriya: Fiziko-matematicheskie nauki [Bulletin of Samara State Technical University. Series: Physical and Mathematical Sciences]. 2004;(26):194-195. (In Russ.)

6. Zaides S.A. Spravochnik po protsessam poverkhnostnogo plasticheskogo deformirovaniya: monografiya [Handbook of surface plastic deformation processes: Monograph]. Vol. 2. Irkutsk: Irkutsk National Research Technical University, 2022, 584 p. (In Russ.)

7. Nguyen Thanh Van, Nguyen Van Hinh, Nguyen Huu Hai. Influence of parameters of a toroidal roller on the geometric characteristics of prints and pressure in the contact zone during reverse surface plastic deformation. Sovremennye materialy, tekhnika i tekhnologii [Modern Materials, Equipment and Technologies]. 2022;(6(45)):99-103. (In Russ.)

8. Ngo Cao Cuong. Intensification of the stress state in the deformation zone during surface plastic deformation of cylindrical parts. Materialy XI Vserossiiskoy nauchno-tekhnicheskoy konferentsii s mezhdunarodnym uchastiem [Proceedings of the 11th All-Russian Scientific and Technical Conference with International Participation]. Irkutsk: Irkutsk National Research Technical University, 2021, pp. 16-26. (In Russ.)

9. Zaides S.A. New methods of surface plastic deformation in manufacturing machine parts. Vestnik Magnitogorskogo gosudarstvennogo tekhnicheskogo universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2018;16(3):129-139. (In Russ.)

10. Ngo Cao Cuong. Study on non-contact deformations under local loading. Vestnik nauki i obrazovaniya Severo-Zapada Rossii [Journal of Science and Education of the North-West of Russia]. 2015;1(3):6-13. (In Russ.)

11. Zaides S.A., Nguyen Huu Hai. Sposob poverkhnostnogo plasticheskogo deformirovaniya naruzhnykh poverkhnostey tel vrashcheniya [Method for surface plastic deformation of the outer surfaces of bodies of revolution]. Patent RU, no. 2758713, 2021.

12. Zaides S.A., Nguyen Huu Hai. Influence of parameters of reverse surface plastic deformation on roughness of hardened parts. Vestnik Voronezhskogo gosudarstvennogo tekhnicheskogo universiteta [Bulletin of Voronezh State Technical University]. 2023;19(1):120-130. (In Russ.)

13. Abramov A.N., Botkin A.V., Balysheva E.G. Influence of physical and chemical properties of a lubricant on surface roughness of a deformable workpiece during drawing. Zagotovitelnye proizvodstva v mashinostroenii [Blank Production in Mechanical Engineering]. 2018;16(7):313-316. (In Russ.)

14. Nikitina E.N. Advantages of the acoustoelasticity method for non-destructive testing of mechanical stresses in machine parts. Vestnik nauchno-tekhnicheskogo razvitiya [Bulletin of Scientific and Technical Development]. 2010;(4(32)):18-28. (In Russ.)

15. Ilyakhinsky A.V., Rodyushkin V.M., Nikitina E.A. On the assessment of acting stresses by the acoustic method during plastic deformation of steel. Transportnye sistemy [Transport Systems]. 2018;(1(17)):52-56. (In Russ.)

16. Zaides S.A., Nguyen Huu Hai. Influence of the initial orientation of the working tool on the stress and strain state during reverse surface plastic deformation. Tekhnologiya metallov [Technology of Metals]. 2022;(12):11-20. (In Russ.)

17. Attila Kossa, László Szabó. Numerical implementation of a novel accurate stress integration scheme of the von Mises elastoplasticity model with combined linear hardening. Finite Elements in Analysis and Design. 2010;46:391-400. https://doi.org/10.1016/j.finel.2009. 12.006

18. Strouboulisa T., Babuŝkab I., Dattaa D.K., Coppsa K., Gangaraja S.K.. A posteriori estimation and adaptive control of the error in the quantity of interest. Part I: A posteriori estimation of the error in the von Mises stress and the stress intensity factor. Computer Methods in Applied Mechanics and Engineering. 2000;181:261-294. https://doi.org/10.1016/S0045-7825(99)00077-8

19. Francesco Farina, Andrea Camisa, Andrea Testa, Ivano Notarnicola, Giuseppe Notarstefano. DISROPT: a Python framework for distributed optimization. IFAC-PapersOnLine. 2020;53:2666-2671. https://doi.org/ 10.1016/j.ifacol.2020.12.382

20. Antonio Benítez-Hidalgo, Antonio J. Nebro, José García-Nieto, Izaskun Oregi, Javier Del Ser. jMetalPy: A Python framework for multi-objective optimization with metaheuristics. Swarm and Evolutionary Computation. 2019;51:100598.