Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints
Abstract This study introduces a machine tool rotary axis error identification method that considers the constraints of the R-test theoretical model. First, a general modeling approach for the R-test was developed based on coordinate transformation theory, and a theoretical model was established for...
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| Format: | Article |
| Language: | English |
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Springer
2025-04-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-025-06807-7 |
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| _version_ | 1850202716379283456 |
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| author | Hongxu Chen Xiaobing Hu Yan Liu Feng Tan Qihao Liao |
| author_facet | Hongxu Chen Xiaobing Hu Yan Liu Feng Tan Qihao Liao |
| author_sort | Hongxu Chen |
| collection | DOAJ |
| description | Abstract This study introduces a machine tool rotary axis error identification method that considers the constraints of the R-test theoretical model. First, a general modeling approach for the R-test was developed based on coordinate transformation theory, and a theoretical model was established for a four-sensor R-test. Then, theoretical constraints were considered, and multi-position measurement data were used across the entire measurement range to identify installation parameters. This approach improved the prediction accuracy of the transformation matrix while ensuring compliance with the theoretical model constraints. Furthermore, the effects of the proposed method, the least squares method, and the direct use of design values on the accuracy of the transformation matrix were analyzed through experiments. Finally, the geometric errors of the machine tool rotary axes were identified, and the effectiveness of the proposed method was verified by comparing experimental values with predicted values. This study not only presented a theoretical analysis method in addition to least squares identification but also providing a novel approach for identifying geometric errors in the machine tool’s rotary axes. While both the proposed method and the least squares method demonstrated high prediction accuracy, the proposed method proved more effective for small errors in machine tools and satisfied theoretical constraints. |
| format | Article |
| id | doaj-art-3055a168c0804ef3aeeca6d0bc64def3 |
| institution | OA Journals |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-3055a168c0804ef3aeeca6d0bc64def32025-08-20T02:11:42ZengSpringerDiscover Applied Sciences3004-92612025-04-017412210.1007/s42452-025-06807-7Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraintsHongxu Chen0Xiaobing Hu1Yan Liu2Feng Tan3Qihao Liao4School of Mechanical and Electrical Engineering, Yibin UniversitySchool of Mechanical Engineering, Sichuan UniversitySichuan Pushi Ningjiang Machine Tool Works Co., Ltd.School of Advanced Manufacturing Engineering, Chongqing University of Posts and TelecommunicationsSchool of Mechanical and Electrical Engineering, Yibin UniversityAbstract This study introduces a machine tool rotary axis error identification method that considers the constraints of the R-test theoretical model. First, a general modeling approach for the R-test was developed based on coordinate transformation theory, and a theoretical model was established for a four-sensor R-test. Then, theoretical constraints were considered, and multi-position measurement data were used across the entire measurement range to identify installation parameters. This approach improved the prediction accuracy of the transformation matrix while ensuring compliance with the theoretical model constraints. Furthermore, the effects of the proposed method, the least squares method, and the direct use of design values on the accuracy of the transformation matrix were analyzed through experiments. Finally, the geometric errors of the machine tool rotary axes were identified, and the effectiveness of the proposed method was verified by comparing experimental values with predicted values. This study not only presented a theoretical analysis method in addition to least squares identification but also providing a novel approach for identifying geometric errors in the machine tool’s rotary axes. While both the proposed method and the least squares method demonstrated high prediction accuracy, the proposed method proved more effective for small errors in machine tools and satisfied theoretical constraints.https://doi.org/10.1007/s42452-025-06807-7R-testTheoretical modelingFive-axis machine toolGeometric error identificationRotary axis |
| spellingShingle | Hongxu Chen Xiaobing Hu Yan Liu Feng Tan Qihao Liao Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints Discover Applied Sciences R-test Theoretical modeling Five-axis machine tool Geometric error identification Rotary axis |
| title | Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints |
| title_full | Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints |
| title_fullStr | Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints |
| title_full_unstemmed | Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints |
| title_short | Geometric errors identification of the machine tool rotary axes considering R-test theoretical model constraints |
| title_sort | geometric errors identification of the machine tool rotary axes considering r test theoretical model constraints |
| topic | R-test Theoretical modeling Five-axis machine tool Geometric error identification Rotary axis |
| url | https://doi.org/10.1007/s42452-025-06807-7 |
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