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Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism
The solution of the dynamic equations of the six-axis accelerometer is a prerequisite for sensor calibration, structural optimization, and practical application. However, the forward dynamic equations (FDEs) and inverse dynamic equations (IDEs) of this type of system have not been completely solved...
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/PMC7795551/ https://www.ncbi.nlm.nih.gov/pubmed/33401430 http://dx.doi.org/10.3390/s21010233 |
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author | Wang, Linkang You, Jingjing Yang, Xiaolong Chen, Huaxin Li, Chenggang Wu, Hongtao |
author_facet | Wang, Linkang You, Jingjing Yang, Xiaolong Chen, Huaxin Li, Chenggang Wu, Hongtao |
author_sort | Wang, Linkang |
collection | PubMed |
description | The solution of the dynamic equations of the six-axis accelerometer is a prerequisite for sensor calibration, structural optimization, and practical application. However, the forward dynamic equations (FDEs) and inverse dynamic equations (IDEs) of this type of system have not been completely solved due to the strongly nonlinear coupling relationship between the inputs and outputs. This article presents a comprehensive study of the FDEs and IDEs of the six-axis accelerometer based on a parallel mechanism. Firstly, two sets of dynamic equations of the sensor are constructed based on the Newton–Euler method in the configuration space. Secondly, based on the analytical solution of the sensor branch chain length, the coordination equation between the output signals of the branch chain is constructed. The FDEs of the sensor are established by combining the coordination equations and two sets of dynamic equations. Furthermore, by introducing generalized momentum and Hamiltonian function and using Legendre transformation, the vibration differential equations (VDEs) of the sensor are derived. The VDEs and Newton–Euler equations constitute the IDEs of the system. Finally, the explicit recursive algorithm for solving the quaternion in the equation is given in the phase space. Then the IDEs are solved by substituting the quaternion into the dynamic equations in the configuration space. The predicted numerical results of the established FDEs and IDEs are verified by comparing with virtual and actual experimental data. The actual experiment shows that the relative errors of the FDEs and the IDEs constructed in this article are 2.21% and 7.65%, respectively. This research provides a new strategy for further improving the practicability of the six-axis accelerometer. |
format | Online Article Text |
id | pubmed-7795551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77955512021-01-10 Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism Wang, Linkang You, Jingjing Yang, Xiaolong Chen, Huaxin Li, Chenggang Wu, Hongtao Sensors (Basel) Article The solution of the dynamic equations of the six-axis accelerometer is a prerequisite for sensor calibration, structural optimization, and practical application. However, the forward dynamic equations (FDEs) and inverse dynamic equations (IDEs) of this type of system have not been completely solved due to the strongly nonlinear coupling relationship between the inputs and outputs. This article presents a comprehensive study of the FDEs and IDEs of the six-axis accelerometer based on a parallel mechanism. Firstly, two sets of dynamic equations of the sensor are constructed based on the Newton–Euler method in the configuration space. Secondly, based on the analytical solution of the sensor branch chain length, the coordination equation between the output signals of the branch chain is constructed. The FDEs of the sensor are established by combining the coordination equations and two sets of dynamic equations. Furthermore, by introducing generalized momentum and Hamiltonian function and using Legendre transformation, the vibration differential equations (VDEs) of the sensor are derived. The VDEs and Newton–Euler equations constitute the IDEs of the system. Finally, the explicit recursive algorithm for solving the quaternion in the equation is given in the phase space. Then the IDEs are solved by substituting the quaternion into the dynamic equations in the configuration space. The predicted numerical results of the established FDEs and IDEs are verified by comparing with virtual and actual experimental data. The actual experiment shows that the relative errors of the FDEs and the IDEs constructed in this article are 2.21% and 7.65%, respectively. This research provides a new strategy for further improving the practicability of the six-axis accelerometer. MDPI 2021-01-01 /pmc/articles/PMC7795551/ /pubmed/33401430 http://dx.doi.org/10.3390/s21010233 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 Wang, Linkang You, Jingjing Yang, Xiaolong Chen, Huaxin Li, Chenggang Wu, Hongtao Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title | Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title_full | Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title_fullStr | Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title_full_unstemmed | Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title_short | Forward and Inverse Dynamics of a Six-Axis Accelerometer Based on a Parallel Mechanism |
title_sort | forward and inverse dynamics of a six-axis accelerometer based on a parallel mechanism |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795551/ https://www.ncbi.nlm.nih.gov/pubmed/33401430 http://dx.doi.org/10.3390/s21010233 |
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