Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness

Abstract Industrial robots have become a crucial tool for milling large and complex surfaces. The dynamic characteristics of a robotic structure significantly influence milling accuracy and efficiency. Accurate identification of these dynamic parameters during operation is essential for vibration su...

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Main Authors: Yongkang Jiao, Xubing Chen, Yili Peng, Xinyong Mao, Qiushuang Guo
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-95339-6
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author Yongkang Jiao
Xubing Chen
Yili Peng
Xinyong Mao
Qiushuang Guo
author_facet Yongkang Jiao
Xubing Chen
Yili Peng
Xinyong Mao
Qiushuang Guo
author_sort Yongkang Jiao
collection DOAJ
description Abstract Industrial robots have become a crucial tool for milling large and complex surfaces. The dynamic characteristics of a robotic structure significantly influence milling accuracy and efficiency. Accurate identification of these dynamic parameters during operation is essential for vibration suppression and enhancing machining performance. Notably, the dynamic characteristics of a robot in operation differ from those in a static state. Operational modal analysis (OMA) enables the identification of structural dynamic parameters under operating conditions, but it necessitates input signals that approximate white noise, which is not met by the excitation forces during typical robot operations. Moreover, OMA is primarily applied to fixed structures, such as buildings and bridges, whereas the dynamic characteristics of robots vary as their poses change during operation. To address these challenges, this paper proposes an autonomous modal analysis method that considers the dynamic spatial sensitivity of robots and the randomness of the excitation frequency band and direction. Firstly, to mitigate the impact of pose changes on modal parameter identification, a method for predicting the sensitivity of natural frequencies based on structural modal shapes is proposed. This approach limits the range of the robot’s self-excitation motion based on dynamic spatial sensitivity analysis. Secondly, the necessary condition for the randomness of the excitation force direction is established, requiring that the torque projection matrix be of full rank. Building on this, a broadband random signal meeting the requirements of white noise is generated through multi-joint random acceleration and deceleration movements. Finally, the efficacy of the proposed autonomous modal analysis method is validated through multi-joint combined self-excitation modal analysis experiments.
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spelling doaj-art-d134779ea6974dc1957447320d02a36d2025-08-20T03:10:09ZengNature PortfolioScientific Reports2045-23222025-04-0115111710.1038/s41598-025-95339-6Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomnessYongkang Jiao0Xubing Chen1Yili Peng2Xinyong Mao3Qiushuang Guo4School of mechanical and electrical engineering, Wuhan Institute of TechnologySchool of mechanical and electrical engineering, Wuhan Institute of TechnologySchool of mechanical and electrical engineering, Wuhan Institute of TechnologySchool of Mechanical Science and Engineering, Huazhong University of Science and TechnologySchool of Mechanical Science and Engineering, Huazhong University of Science and TechnologyAbstract Industrial robots have become a crucial tool for milling large and complex surfaces. The dynamic characteristics of a robotic structure significantly influence milling accuracy and efficiency. Accurate identification of these dynamic parameters during operation is essential for vibration suppression and enhancing machining performance. Notably, the dynamic characteristics of a robot in operation differ from those in a static state. Operational modal analysis (OMA) enables the identification of structural dynamic parameters under operating conditions, but it necessitates input signals that approximate white noise, which is not met by the excitation forces during typical robot operations. Moreover, OMA is primarily applied to fixed structures, such as buildings and bridges, whereas the dynamic characteristics of robots vary as their poses change during operation. To address these challenges, this paper proposes an autonomous modal analysis method that considers the dynamic spatial sensitivity of robots and the randomness of the excitation frequency band and direction. Firstly, to mitigate the impact of pose changes on modal parameter identification, a method for predicting the sensitivity of natural frequencies based on structural modal shapes is proposed. This approach limits the range of the robot’s self-excitation motion based on dynamic spatial sensitivity analysis. Secondly, the necessary condition for the randomness of the excitation force direction is established, requiring that the torque projection matrix be of full rank. Building on this, a broadband random signal meeting the requirements of white noise is generated through multi-joint random acceleration and deceleration movements. Finally, the efficacy of the proposed autonomous modal analysis method is validated through multi-joint combined self-excitation modal analysis experiments.https://doi.org/10.1038/s41598-025-95339-6Industrial robotAutonomous modal analysisDynamic Spatial sensitivityTorque projection matrix
spellingShingle Yongkang Jiao
Xubing Chen
Yili Peng
Xinyong Mao
Qiushuang Guo
Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
Scientific Reports
Industrial robot
Autonomous modal analysis
Dynamic Spatial sensitivity
Torque projection matrix
title Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
title_full Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
title_fullStr Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
title_full_unstemmed Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
title_short Autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
title_sort autonomous modal analysis method for industrial robots considering dynamic spatial sensitivity and excitation randomness
topic Industrial robot
Autonomous modal analysis
Dynamic Spatial sensitivity
Torque projection matrix
url https://doi.org/10.1038/s41598-025-95339-6
work_keys_str_mv AT yongkangjiao autonomousmodalanalysismethodforindustrialrobotsconsideringdynamicspatialsensitivityandexcitationrandomness
AT xubingchen autonomousmodalanalysismethodforindustrialrobotsconsideringdynamicspatialsensitivityandexcitationrandomness
AT yilipeng autonomousmodalanalysismethodforindustrialrobotsconsideringdynamicspatialsensitivityandexcitationrandomness
AT xinyongmao autonomousmodalanalysismethodforindustrialrobotsconsideringdynamicspatialsensitivityandexcitationrandomness
AT qiushuangguo autonomousmodalanalysismethodforindustrialrobotsconsideringdynamicspatialsensitivityandexcitationrandomness