Investigation of the Peculiarities of Deformation and Fracture of Metals Obtained on the Basis of 3D Printing with Registration of an Acoustic Emission Signal

Author:

Anosov Maksim S.1ORCID,Kabaldin Yury G.1,Shatagin Dmitrii A.1,Ryabov Dmitry A.1,Kolchin Pavel1

Affiliation:

1. Nizhny Novgorod State Technical University

Abstract

The paper investigates the features of deformation and fracture of steels obtained using the technology of 3D printing by electric arc surfacing based on the registration of the acoustic emission signal. With a decrease in the test temperature of 07Cr25Ni13 steel, a decrease in the work expended in stretching the specimen is observed, both at the stage of elastic deformation and at the stage of strain hardening. It was found that the most informative characteristic parameters of the AE signal include: the pulse count rate N, the total count NΣ, and the AE signal entropy. With a decrease in the test temperature, there is a significant increase in the intensity of the AE signal, the total number of pulses at all stages of deformation and destruction of steel. The obtained regularities of changes in the characteristic parameters of the AE signal can be used as diagnostic features, both in assessing the stage of deformation and destruction of the material, and the structural state of the material. Fractographic studies have shown a significant decrease in the tough component of 08Mn2Si steel with a decrease in the test temperature. The fracture mechanisms of 07Cr25Ni13 steel change insignificantly with decreasing temperature, however, a significant decrease in the ductility of the metal is observed, as evidenced by a decrease in the size of ductile fracture cups.

Publisher

Trans Tech Publications, Ltd.

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

Reference8 articles.

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3. N.A. Semashko, B.N. Maryin, Acoustic emission in experimental materials science/ed. N.A. Semashko.- M .: mechanical engineering, (2002).

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5. D.A. Shatagin, M.S. Anosov, Yu.G. Kabaldin, A.A. Galkin, N.S. Klochkova, Development of a digital twin of the process of 3D printing by electric arc surfacing on a CNC machine using machine learning methods and numerical simulation. Trends in the development of science and education, Vol. 67-2 (2020) 55-62.

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