Machine vision in in situ estimation of inhomogeneity parameters of anisotropic SLM products during tensile behaviour

An original method for calculating in situ characteristics of inhomogeneity of anisotropic
materials based on machine vision technology (photogrammetry) is proposed. The objects were
samples of powder alloys 316L and Inconel 718, manufactured using selective laser fusion (SLM)
technology and subjected to static stretching.
The technique is based on the joint use of hardening curves in the calculation of parameters, based on the results of in situ determination of the intensities of true stresses and deformations in individual micro-volumes of samples. Cross sections of a dividing grid applied to the surface of the samples were used as such micro-volumes.
Information about the geometry of the cells of the dividing grid, which changed during stretching, was obtained in the measuring unit from the results of photogrammetry - measurements of digital images of the dividing grid obtained during photofixation of the
sample during stretching. In the calculation block, the equations of dependence of the material heterogeneity index on mechanical properties and the characteristics of the unevenness of its plastic deformation on the intensity of acting stresses and deformations are obtained using the technique.
The use of mathematical algorithms for optimizing photogrammetry and programming the calculation block in Python JAVA will automate the process of calculating the obtained equations and their parameters and, as a result, create an extensive database of anisotropy characteristics and heterogeneity of properties of products manufactured by the SLM method.
This will ensure the creation of theoretical foundations for in-depth analysis and reasonable forecasting of the impact of technological anisotropy and heterogeneity of the properties of SLM products on their in situ performance.

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