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Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling
The flexibility of the joint drive system of an industrial robot can cause vibration at the end part, which can lead to motion errors. A method to predict the vibration during the motion of the robot arm is proposed considering the robot joint flexibility. The method combines the internal transfer f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414790/ https://www.ncbi.nlm.nih.gov/pubmed/36015931 http://dx.doi.org/10.3390/s22166170 |
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author | Li, Jianlong Wang, Dongxiao Wu, Xing Xu, Kai Liu, Xiaoqin |
author_facet | Li, Jianlong Wang, Dongxiao Wu, Xing Xu, Kai Liu, Xiaoqin |
author_sort | Li, Jianlong |
collection | PubMed |
description | The flexibility of the joint drive system of an industrial robot can cause vibration at the end part, which can lead to motion errors. A method to predict the vibration during the motion of the robot arm is proposed considering the robot joint flexibility. The method combines the internal transfer function of the drive system and the identification of parameters under external excitation. Firstly, the dynamics of the robot joint system are modeled by a double inertia elastic system. The joint system transfer function from the electromagnetic torque to the arm vibration is obtained according to the dynamics model. To solve the unknown parameters in the transfer function, a vibration dynamics model of the joint arm under the external forces on the arm is developed. According to this model, the equivalent stiffness, damping and load inertia of the joint can be obtained by the direct parametric method. Then, the vibration spectrum of the robot arm is derived from the motor electromagnetic torque and joint dynamics models were used to predict the vibration spectrum of the robot arm. The experiments were conducted on a single-joint robot testbed, and on an articulated industrial robot. In both experiments, the key parameters in the system were determined by impact experiments. Then, the vibration signal of the arm during the robot motion was obtained by electromagnetic torque prediction. The predicted vibration signals are analyzed in comparison with the actual vibration signals. The experimental results both show the validity of the vibration prediction. |
format | Online Article Text |
id | pubmed-9414790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94147902022-08-27 Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling Li, Jianlong Wang, Dongxiao Wu, Xing Xu, Kai Liu, Xiaoqin Sensors (Basel) Article The flexibility of the joint drive system of an industrial robot can cause vibration at the end part, which can lead to motion errors. A method to predict the vibration during the motion of the robot arm is proposed considering the robot joint flexibility. The method combines the internal transfer function of the drive system and the identification of parameters under external excitation. Firstly, the dynamics of the robot joint system are modeled by a double inertia elastic system. The joint system transfer function from the electromagnetic torque to the arm vibration is obtained according to the dynamics model. To solve the unknown parameters in the transfer function, a vibration dynamics model of the joint arm under the external forces on the arm is developed. According to this model, the equivalent stiffness, damping and load inertia of the joint can be obtained by the direct parametric method. Then, the vibration spectrum of the robot arm is derived from the motor electromagnetic torque and joint dynamics models were used to predict the vibration spectrum of the robot arm. The experiments were conducted on a single-joint robot testbed, and on an articulated industrial robot. In both experiments, the key parameters in the system were determined by impact experiments. Then, the vibration signal of the arm during the robot motion was obtained by electromagnetic torque prediction. The predicted vibration signals are analyzed in comparison with the actual vibration signals. The experimental results both show the validity of the vibration prediction. MDPI 2022-08-18 /pmc/articles/PMC9414790/ /pubmed/36015931 http://dx.doi.org/10.3390/s22166170 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Jianlong Wang, Dongxiao Wu, Xing Xu, Kai Liu, Xiaoqin Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title | Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title_full | Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title_fullStr | Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title_full_unstemmed | Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title_short | Vibration Prediction of the Robotic Arm Based on Elastic Joint Dynamics Modeling |
title_sort | vibration prediction of the robotic arm based on elastic joint dynamics modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414790/ https://www.ncbi.nlm.nih.gov/pubmed/36015931 http://dx.doi.org/10.3390/s22166170 |
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