Журнал Российского общества по неразрушающему контролю и технической диагностике
The journal of the Russian society for non-destructive testing and technical diagnostic
 
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21 | 09 | 2026
2016, 01 январь (January)

DOI: 10.14489/td.2018.01.pp.032-038

 

Kabaldin Yu. G., Shatagin D. A., Anosov M. S., Zhelonkin M. V., Golovin A. A.
CLASSIFICATION AND IDENTIFICATION OF ACOUSTIC EMISSION SIGNALS UNDER DEFORMATION AND FRACTURE OF MATERIALS AT LOW TEMPERATURES ON THE BASIS OF THE APPROACHES OF ARTIFICIAL INTELLIGENCE AND NONLINEAR DYNAMICS
(pp. 32-38)

Abstract. The article presents the results of the investigation of the process of deformation and fracture of metals in conditions of low temperatures. It gives a schematic diagram of the software developed for the detection and classification of pulses in the signal of acoustic emission (AE), including signal filtering, preparing it for analysis, calculation of signal parameters (pulse energy, entropy, and the fractal dimension) while constructing loading diagram. According to the results of the AE signal analysis, the characteristic signs of impulses with viscous, brittle and mixed fracture are distinguished during the stretching of various groups of materials. The results of acoustic analysis are confirmed by fractographic studies of specimen destruction surfaces. Based on the identified signs, classification and identification of the AE signal using neural networks was carried out. Studies were conducted on samples of steel 45 (preloaded without the preload) when stretched in a temperature range of –30 °C up to + 20 °C, in order to determine the mechanism of deformation and fracture in real time. New criteria for estimating the stability of the structural state of metals by fractal dimension and information entropy are proposed. As studies have shown, the application of approaches to nonlinear dynamics makes it possible to evaluate structural transitions at various scale levels.

Keywords: acoustic emission, low temperature, pulses, wavelet, neural network, attractors, information entropy, the mechanism of destruction, classification.

 

Yu. G. Kabaldin, D. A. Shatagin, M. S. Anosov, M. V. Zhelonkin, A. A. Golovin (Nizhny Novgorod State Technical University n.a. R. E. Alekseev, Nizhny Novgorod, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.  

 

 

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DOI: 10.14489/td.2016.01.pp.059-062

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