Comparison of Two Machine Learning Models for Predicting Volumetric Errors From On-The-Fly R-Test Type Device Data and Virtual End Point Constraints

Comparison of Two Machine Learning Models for Predicting Volumetric Errors From On-The-Fly R-Test Type Device Data and Virtual End Point Constraints

On-the-fly virtual end-point constraints consists in moving all five axes of the machine tool while nominally maintaining the coincidence of a sensing head centre point with a master ball centre attached to the workpiece table. The sensing head detects the deviations from the nominal coincidence as...

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Bibliographic Details
Main Authors: Min Zeng, J. R. R. Mayer, Miao Feng, Elie Bitar-Nehme, Xuan Truong Duong
Format: Article
Language:English
Published: Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT 2025-05-01
Series:Journal of Machine Engineering
Subjects:
machine learning
five-axis machine tool
volumetric errors
r-test
Online Access:http://jmacheng.not.pl/Comparison-of-Two-Machine-Learning-Models-for-Predicting-Volumetric-Errors-From-On,203805,0,2.html
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