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

Yongkang Jiao1, Xubing Chen1,2, Yili Peng3,4

  • 1School of mechanical and electrical engineering, Wuhan Institute of Technology, Wuhan, 430205, China.

Scientific Reports
|April 12, 2025
PubMed
Summary

This study introduces an autonomous modal analysis method for industrial robots, enabling accurate dynamic parameter identification during operation. The method enhances milling accuracy and efficiency by addressing pose variations and random excitation forces.

Keywords:
Autonomous modal analysisDynamic Spatial sensitivityIndustrial robotTorque projection matrix

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Area of Science:

  • Mechanical Engineering
  • Robotics
  • Vibration Analysis

Background:

  • Industrial robots are vital for milling complex surfaces, but their dynamic characteristics impact machining performance.
  • Accurate identification of dynamic parameters during operation is crucial for vibration suppression and efficiency.
  • Existing operational modal analysis (OMA) methods are unsuitable for robots due to non-white noise excitation and changing poses.

Purpose of the Study:

  • To propose an autonomous modal analysis method for industrial robots that accounts for dynamic spatial sensitivity and random excitation.
  • To enable accurate identification of dynamic parameters under operational conditions, despite pose variations.

Main Methods:

  • A method for predicting natural frequency sensitivity based on modal shapes to limit self-excitation motion range.
  • Establishing conditions for random excitation force direction using a full-rank torque projection matrix.
  • Generating broadband random signals via multi-joint random acceleration/deceleration for white noise excitation.

Main Results:

  • The proposed method effectively mitigates the impact of pose changes on modal parameter identification.
  • Broadband random excitation signals meeting white noise requirements were successfully generated.
  • Experimental validation confirmed the efficacy of the autonomous modal analysis method.

Conclusions:

  • The developed autonomous modal analysis method enhances the accuracy and efficiency of milling operations with industrial robots.
  • This approach provides a robust solution for identifying robot dynamic parameters under realistic operating conditions.