The article provides the system of interaction of dynamic processes during deep profile grinding of complex profiles on a multiaxis machine, the influence of dynamic processes on the quality of the surface layer, the endurance limit of the gas-turbine engine blade. The method presented allows to assign corresponding grinding modes based on the forecast of the dynamics of elastic, thermal and working processes in a thermomechanical system. This technique allows to control the process of deep profile grinding to achieve the specified parameters of surface quality, the endurance limit of the blade and increase process efficiency.
It is defined that during the machining of complex surfaces in parts operating under large fluctuating loads, in critical transition areas of profile conjugate surfaces there are formed local technological concentrators of stresses contributing to formation, development of fatigue cracks and to further destruction of parts in the course of operation. Such phenomena are discovered, for instance, at high-loaded gear teeth machining, at turbine blade profile surface machining, at manufacturing large-modular tapered threads and other parts having complex profile surfaces.
There are developed and introduced methods for value decrease of such stress concentrators on the basis of the application of different methods for local surface plastic deformation of a surface layer in transition areas of profiles. As a result the probability of fatigue crack formation decreased considerably and fatigue strength in parts machined increased essentially.
To study the face milling of hardened steel, the paper considers the chemical composition of the processed material, as well as metal-cutting, measuring equipment and tools. A full factorial experiment of face milling was carried out by the method of mathematical planning and matrices of levels of variation and planning of independent variables were compiled. The flatness of the samples was measured and the causes of plastic deformation were determined. To find an adequate mathematical model of flatness, a regression analysis was performed, and the correlation analysis revealed the closeness of the relationship between the variables under one-and two-factor influence on the response function. The hypersurfaces and lines of the function levels are projected, which made it possible to determine the optimal and effective cutting conditions graphically and analytically.
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