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Improved subspace modal identification of industrial robots

Yuting Qiao, Junyi Cao, Guohui Huang, Huan Liu, Yaguo Lei, Qinghua Liu

发表年份
2023
引用次数
5

摘要

Abstract Industrial robots have become key components for manufacturing automations due to their larger workspaces and flexibility. However, low stiffness and high compliance of industrial robots may inevitably lead to vibration by self‐excitation or periodic force dependent on workspace configuration. Therefore, the knowledge of the robot's modal properties should be accurately required to enhance the operation accuracy of industrial robots. To improve the identification accuracy of experimental modal parameters of field industrial robots, an improved subspace identification method is proposed to perform nonlinear iterative optimization for updating the state parameters of industrial robots. Experimental response measurement of a six‐degrees‐of‐freedom industrial robot is carried out to obtain modal parameters under various poses. The identification results of the improved subspace modal method are preferable to that of the traditional method. Moreover, the reconstructed three‐dimension working frequency space is presented to exactly characterize experimental modal frequencies throughout its workspace. The proposed method effectively improves the identification accuracy of modal parameters when compared with the traditional algorithms and the influence of robots' pose change on modal parameters is also investigated by experimental modal measurements.

关键词

RobotWorkspaceModalSubspace topologyIdentification (biology)Modal analysisIndustrial robotModal analysis using FEMVibrationModal testing

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