Kinematic error model of a 3-PUU parallel mechanism for translational motion
[Display omitted] •A revised kinematic error model, link-orientation-based joint error model (LOBJEM), is proposed.•The sensitivity of each error term in the working space is analyzed.•The compensation result of LOBJEM is better than the original error model.•A backpropagation neural network is cons...
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| Vydáno v: | Measurement : journal of the International Measurement Confederation Ročník 202; s. 111853 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.10.2022
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| Témata: | |
| ISSN: | 0263-2241, 1873-412X |
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| Abstract | [Display omitted]
•A revised kinematic error model, link-orientation-based joint error model (LOBJEM), is proposed.•The sensitivity of each error term in the working space is analyzed.•The compensation result of LOBJEM is better than the original error model.•A backpropagation neural network is constructed to estimate the residual error caused by NGPs.•The final remained error is reduced to 0.03 mm.
Accuracy of parallel kinematic machine (PKM) is affected by geometric parameters (GPs) and non-geometric parameters (NGPs). For GPs, the use kinematic error model (KEM) to calibrate these errors has been studied, but few of them have considered the influence of the linkage posture. In this paper, link-orientation-based joint error model (LOBJEM) and sensitivity analysis are presented. In LOBJEM, the original KEM, which is constant joint error model (CJEM), is derived first. The angle between each link and the Z axis is considered as the parameter to adjust the KEM to derive LOBJEM and it can cause the value of joint error to vary with the position of end effector. The calibration process includes measuring the positioning error by a laser interferometer, identifying the error terms using least square method and compensating by the numerical control code (NC-code). The error model and calibration process have been realized on the delta robot 3D printer. Compared with the CJEM, the residual error of LOBJEM was reduced from 75% to 60% of the original error. To estimate the positioning errors caused by NGPs, we constructed a backpropagation neural network model, which can reduce the final residual error to 25% of the original error. |
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| AbstractList | [Display omitted]
•A revised kinematic error model, link-orientation-based joint error model (LOBJEM), is proposed.•The sensitivity of each error term in the working space is analyzed.•The compensation result of LOBJEM is better than the original error model.•A backpropagation neural network is constructed to estimate the residual error caused by NGPs.•The final remained error is reduced to 0.03 mm.
Accuracy of parallel kinematic machine (PKM) is affected by geometric parameters (GPs) and non-geometric parameters (NGPs). For GPs, the use kinematic error model (KEM) to calibrate these errors has been studied, but few of them have considered the influence of the linkage posture. In this paper, link-orientation-based joint error model (LOBJEM) and sensitivity analysis are presented. In LOBJEM, the original KEM, which is constant joint error model (CJEM), is derived first. The angle between each link and the Z axis is considered as the parameter to adjust the KEM to derive LOBJEM and it can cause the value of joint error to vary with the position of end effector. The calibration process includes measuring the positioning error by a laser interferometer, identifying the error terms using least square method and compensating by the numerical control code (NC-code). The error model and calibration process have been realized on the delta robot 3D printer. Compared with the CJEM, the residual error of LOBJEM was reduced from 75% to 60% of the original error. To estimate the positioning errors caused by NGPs, we constructed a backpropagation neural network model, which can reduce the final residual error to 25% of the original error. |
| ArticleNumber | 111853 |
| Author | Ke, Jian-Dong Wang, Yu-Jen Tsai, Jhy-Cherng |
| Author_xml | – sequence: 1 givenname: Jian-Dong orcidid: 0000-0003-4300-2682 surname: Ke fullname: Ke, Jian-Dong organization: Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan – sequence: 2 givenname: Yu-Jen surname: Wang fullname: Wang, Yu-Jen email: yjwang@mail.nsysu.edu.tw organization: Department of Mechanical and Electromechanical Engineering, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan – sequence: 3 givenname: Jhy-Cherng orcidid: 0000-0002-4290-8952 surname: Tsai fullname: Tsai, Jhy-Cherng email: jctsai@dragon.nchu.edu.tw organization: Department of Mechanical Engineering, National Chung Hsing University, Taichung 40227, Taiwan |
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| Keywords | Parallel kinematic machine Error estimation Backpropagation neural network Kinematic error model Vertically distributed 3-PUU PKM |
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•A revised kinematic error model, link-orientation-based joint error model (LOBJEM), is proposed.•The sensitivity of each error term in the... |
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| SubjectTerms | Backpropagation neural network Error estimation Kinematic error model Parallel kinematic machine Vertically distributed 3-PUU PKM |
| Title | Kinematic error model of a 3-PUU parallel mechanism for translational motion |
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