Abstract

The main purpose of the article is development of method for determining the fractional composition of the shots during shot peen hardening. During peen hardening of aluminum aviation parts the deformation of spatial form of the part usually occurs due to the non-homogeneous compaction of their structural elements. Form straightening of hardened parts by methods of elastic-plastic deformation is unacceptable, as there may be a loss of hardening effect. A promising task is to predict the hardening process using finite element modeling, which will allow the use of preventive deformation in order to minimize the deformation. Also, finite element modeling of the shot hardening process can significantly reduce the costs associated with the manufacture of structurally similar samples when determining the predicted deformations of hardened parts. The proposed method allows the use of technical vision in the preparation of input data when modeling the hardening process, as well as to control the quality of the shot used in the hardening process. The study was carried out using machine vision equipment of the National Instruments company. This equipment is based on the NI Smart Camera, which allows interactive collection of video images and their processing. The measured sample is 500 grams of shot used in production for hardening aircraft parts. The proposed method consists obtaining of data array of the fractional composition using machine vision and analysis in a prepared C++ software module that displays the obtained data in the form of an Excel table. The obtained results were also verified using the equipment made on a 3D printer, which showed that the relative deviations of the calculated model data from experimental studies do not exceed 10%, which indicates sufficient accuracy of the developed methodology.

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