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Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method
In order to investigate the thermal effect of a servo axis’ positioning error on the accuracy of machine tools, an empirical modeling method was proposed, which considers both the geometric and thermal positioning error. Through the analysis of the characteristics of the positioning error curves, th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919671/ https://www.ncbi.nlm.nih.gov/pubmed/33672093 http://dx.doi.org/10.3390/mi12020201 |
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author | Li, Yang Shi, Hexuan Ji, Shijun Liang, Fusheng |
author_facet | Li, Yang Shi, Hexuan Ji, Shijun Liang, Fusheng |
author_sort | Li, Yang |
collection | PubMed |
description | In order to investigate the thermal effect of a servo axis’ positioning error on the accuracy of machine tools, an empirical modeling method was proposed, which considers both the geometric and thermal positioning error. Through the analysis of the characteristics of the positioning error curves, the initial geometric positioning error was modeled with polynomial fitting, while the thermal positioning error was built with an empirical modeling method. Empirical modeling maps the relationship between the temperature points and thermal error directly, where the multi-collinearity among the temperature variables exists. Therefore, fuzzy clustering combined with principal component regression (PCR) is applied to the thermal error modeling. The PCR model can preserve information from raw variables and eliminate the effect of multi-collinearity on the error model to a certain degree. The advantages of this modeling method are its high-precision and strong robustness. Experiments were conducted on a three-axis machine tool. A criterion was also proposed to select the temperature-sensitivity points. The fitting accuracy of the comprehensive error modeling could reach about 89%, and the prediction accuracy could reach about 86%. The proposed modeling method was proven to be effective and accurate enough to predict the positioning error at any time during the machine tool operation. |
format | Online Article Text |
id | pubmed-7919671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79196712021-03-02 Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method Li, Yang Shi, Hexuan Ji, Shijun Liang, Fusheng Micromachines (Basel) Article In order to investigate the thermal effect of a servo axis’ positioning error on the accuracy of machine tools, an empirical modeling method was proposed, which considers both the geometric and thermal positioning error. Through the analysis of the characteristics of the positioning error curves, the initial geometric positioning error was modeled with polynomial fitting, while the thermal positioning error was built with an empirical modeling method. Empirical modeling maps the relationship between the temperature points and thermal error directly, where the multi-collinearity among the temperature variables exists. Therefore, fuzzy clustering combined with principal component regression (PCR) is applied to the thermal error modeling. The PCR model can preserve information from raw variables and eliminate the effect of multi-collinearity on the error model to a certain degree. The advantages of this modeling method are its high-precision and strong robustness. Experiments were conducted on a three-axis machine tool. A criterion was also proposed to select the temperature-sensitivity points. The fitting accuracy of the comprehensive error modeling could reach about 89%, and the prediction accuracy could reach about 86%. The proposed modeling method was proven to be effective and accurate enough to predict the positioning error at any time during the machine tool operation. MDPI 2021-02-15 /pmc/articles/PMC7919671/ /pubmed/33672093 http://dx.doi.org/10.3390/mi12020201 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Yang Shi, Hexuan Ji, Shijun Liang, Fusheng Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title | Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title_full | Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title_fullStr | Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title_full_unstemmed | Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title_short | Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method |
title_sort | thermal positioning error modeling of servo axis based on empirical modeling method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7919671/ https://www.ncbi.nlm.nih.gov/pubmed/33672093 http://dx.doi.org/10.3390/mi12020201 |
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