Mr. Elena Yu. Malysheva Profile

Elena Yu. Malysheva

at Moscow State Univ of Technology "STANKIN"

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Author

Publications (4)

Proceedings Article | 20 November 2024 Poster + Paper

A computer vision system for measuring the geometric parameters of helical surfaces obtained by multicoordinate grinding on CNC machines

Petr Pivkin, Anton Yazev, Vladimir Grechishnikov, Ekaterina Nazarenko, Elena Yu. Malysheva, Lyudmila Uvarova, Alexey Nadykto

Proceedings Volume 13241, 1324124 (2024) https://doi.org/10.1117/12.3037374

KEYWORDS: Image processing, Surface finishing, Image segmentation, Computing systems, Computer vision technology, Matrices, Abrasives, Control systems, Cameras

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Helical surfaces are important elements of solid end mills. Their production is carried out using multi-coordinate grinding. Shape errors and reduction in the quality of the screw surface appear due to abrasion, high pressure, and wear of the grinding wheel. Therefore, it is extremely important to measure geometric accuracy, to perform linear and angular measurements, and to study the properties of rake helical surfaces. The paper proposes improvements to monitoring of helical surfaces via the use of a new computer vision system for assessing microtexture on helical surfaces after multiaxis grinding on CNC machines. A computer vision system was developed to evaluate defects on helical surfaces after multi-coordinate grinding on CNC machines, and a comprehensive analysis of existing indicators for recognizing the defect was carried out in a guaranteed range of probability of finding a solution of 99.7% for the distribution density of grinds. To verify the developed method, the accuracy of surfaces obtained by using the one was compared with the measurements carried out using specialized equipment for the control of the accuracy of helical surfaces. A new system for monitoring the accuracy and defects of cutting edges, helical front and rear surfaces allows establishing the main geometric parameters of the cutting edges and cutting wedge such as flute angle and rake angle at the apex using key indicators of the difference in color intensity in the focal zone of the image. When developing this approach, it was found that areas with smaller curvature of the rake surface are more susceptible to the accumulation of helical flute pitch errors after grinding. Experimental studies of the system operation were conducted to provide empirical evidence on helical surfaces after multiaxis grinding on CNC machines, demonstrating excellent convergence and defect recognition accuracy. The accuracy of determining the results of the inclination angles of the microtexture surface after grinding at the control point is 2-2.5 degrees, which allows you to form a comprehensive solution for scanning the surface, which will allow you to apply a simple method of control using a camera in reflected light.

Proceedings Article | 27 November 2023 Poster + Paper

New indicators and standards for measuring of the end mill's helical groove by image processing

Petr Pivkin, Artem Ershov, Vladimir Grechishnikov, Vladimir Kuznetsov, Ekaterina Nazarenko, Elena Yu. Malysheva, Alexey Nadykto

Proceedings Volume 12769, 127691P (2023) https://doi.org/10.1117/12.2690091

KEYWORDS: Image processing, Standards development, Reflection, Optical surfaces, Optical metrology, Inspection

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Proceedings Article | 19 December 2022 Poster + Paper

A new approach of modeling micromachining parts with a shaped generatrix by image processing of tool's cutting surface

Petr Pivkin, Artem Ershov, Vladimir Grechishnikov, Elena Yu. Malysheva, Ekaterina Nazarenko, Xiaohui Jiang, Weicheng Guo, Alexey Nadykto

Proceedings Volume 12319, 1231925 (2022) https://doi.org/10.1117/12.2646534

KEYWORDS: Abrasives, Image processing, Micromachining, Surface finishing, Modeling, Image quality, Cameras, Wavelet transforms, Image filtering, CCD cameras

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Proceedings Article | 19 December 2022 Poster + Paper

Identification of new indicators for recognition of cutting grains and wear of the grinding wheel based on image recogntion

Petr Pivkin, Artem Ershov, Vladimir Grechisnikov, Elena Yu. Malysheva, Ekaterina Nazarenko, Alexey Nadykto

Proceedings Volume 12319, 1231924 (2022) https://doi.org/10.1117/12.2646533

KEYWORDS: Abrasives, Surface finishing, Image filtering, Tunable filters, Optical filters, Algorithm development, Wavelet transforms, Manufacturing, Process modeling, Motion models

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