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Article

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Title

Machine Learning-Based Selection of Measurement Technique for Surface Metrology: A pilot study

Authors

[ 1 ] Instytut Technologii Mechanicznej, Wydział Inżynierii Mechanicznej, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.9] Mechanical engineering

Year of publication

2024

Published in

Metrologia i Probiernictwo

Journal year: 2024 | Journal number: no. 1

Article type

scientific article

Publication language

english

Keywords
EN
  • artificial intelligence
  • machine learning
  • surface metrology
  • data processing
  • coordinate measuring machine
Abstract

EN The study introduces the application of machine learning (ML) for surface texture metrology in decision-making support for measurement system preliminary selection. The paper delves into the intricate data filtering considerations and the diverse metrological parameters involved across different measurement techniques. Tailored to the specifics of the measuring object, surface texture parameters, and factors such as measurement technique and uncertainty, the algorithm developed offers predictive capabilities. Drawing from a database of available metrological devices streamlines the operator's task by predicting the appropriate system before conducting measurements. Preliminary results from the validation of prediction models are also provided.

Pages (from - to)

1 - 9

URL

https://www.gum.gov.pl/wye/content/current-volume/12024/6016,Machine-Learning-Based-Selection-of-Measurement-Technique-for-Surface-Metrology-.html

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

70

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