A.V. Korotitskiy, S.V. Gromov

Currently, shape memory alloys are increasingly used in many fields of engineering and medicine. The technique - are active elements of sensors, thermo-mechanical coupling pipe joints, antenna and frames of different devices. In medicine, shape memory alloys used for the manufacture of paper clips and cords for fast matching bone fractures, archwires, traps for gallstones and many other accessories. Since the functional properties of shape memory alloys are largely determined by their structure, to obtain the desired combination of properties required to establish optimum conditions of thermo-mechanical processing. The process of finding the optimum conditions of thermo-mechanical treatment is characterized by long duration, high labor intensity of metal and verification tests. Therefore, it is urgent is to improve the efficiency of finding the optimal mode of thermo-mechanical processing of shape memory alloys, combined with the high reliability of the experimental results. This work is dedicated to the development of an intelligent system for analyzing recovery in shape memory alloys and the definition of reversible deformation occurring by implementing the shape memory effect and superelasticity effect. In the process, the system performs the following operations: - determining the optimal parameter empirical relationship describing the geometric features of the profile of the sample with automatic 'noise' on the surface roughness; - identification of the profile curvature (1/R) at each point along the contour of the entire sample; - construction of distribution: the degree and extent of induced strain on the reduced length of the sample; - identification of dependencies: the degree of reduction of form and other characteristics of the degree formovosstanovleniya induced strain (εi); - graphical presentation and analysis of the experimental results. For a software implementation has been used algorithm to analyze the geometric parameters of the reversible strain in alloys with shape memory. At the core of the algorithm is a new method for the rapid assessment of the recovery options form. The system is implemented in the desktop version of the programming language # C. Researchers propose to analyze the graph of the reconstructed from the induced strain, additional information describing the quality of the experimental data.