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

作者：Yongkang Jiao, Xubing Chen, Yili Peng, Xinyong Mao, Qiushuang Guo · 发表于：Scientific Reports · 年份：2025 · DOI：10.1038/s41598-025-95339-6 · 被引用次数：3 · 研究领域：Advanced Measurement and Metrology Techniques、Advanced machining processes and optimization、Optical measurement and interference techniques

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, requir...