Intellectual system for automated determination of the quality of natural stones surfaces processing

Authors

  • I.Yu. Cherepanska
  • A.Yu. Sazonov
  • S.V. Kalchuk
  • О.F. Sokolovskyi
  • О.S. Sivaieva

DOI:

https://doi.org/10.31489/2022ph1/15-26

Keywords:

artificial neural networks, roughness, quality, automation, accuracy, speed, measurement

Abstract

This automation of determination of the quality of natural stone surfaces processing is a relevant problem. It provides an intellectual system for automated determination of the quality of processing surfaces of natural stones (ISADQSS), which allows rapid assessment of the quality of stone surfaces, including roughness, with high accuracy and quick action in automatic mode and real time. The measurement result is independent of the humidity and cleanliness of the outer surface. The root mean square error of the proposed ISADQSS does not exceed 5%, the time to determine the value of the roughness is not over 2 s. ISADQSS is based on the principles of synergetic integration of various technical automation devices with different properties – artificial neural networks (ANN) (in the case of their implementation in the form of neuroprocessors), as well as the so-called registrar of main drive currents (RMDC), which is used as a sensor sensitive to changes in the rubbing force of the stone-cutting tool depending on changes in the roughness value of the machined surface. The proposed ISADQSS is an innovative and promising development that combines such advantages as high accuracy and speed, versatility and ease of use.

Additional Files

Published

2022-03-30

Issue

Section

TECHNICAL PHYSICS

Received

2023-11-23