The vibration stability of cantilever mechanism under high-speed rotation directly affects the positioning accuracy. Modal analysis method is usually used to study the vibration stability. However, the traditional experimental modal analysis (EMA) method needs to measure the impulse excitation, while the operational modal analysis (OMA) method needs to satisfy the assumption of white noise. Therefore, the existing modal analysis methods cannot be applied to the study of vibration stability of high-frequency cantilever mechanism. In this paper, the symbolic regression (SR) algorithm is combined with the EMA method, and the robustness analysis and feasibility verification are carried out under the condition of adding noise. The validation of the new method is divided into two parts. In the first part, a three degree of freedom (DOF) linear model is constructed, and the modal parameters identified by SR method and state space method are compared. In the second part, the method is applied to identify the modal parameters of stepped bar. The results are compared with the results of LMS (Siemens’ Testlab). Based on the time-domain response signal only, the modal parameters are extracted by SR, and the main vibration frequency is extracted from the response signal. The system simulation and experimental results show the method provides a possibility to analyze the vibration stability of cantilever structure.
Application of dynamic adaptive technology based on symbolic regression to identify modal parameters of chip sorter