z-logo
open-access-imgOpen Access
Research on Dynamic Balance of Spindle Rotor System Based on Particle Swarm Optimization
Author(s) -
Zhan Wang,
Dongzheng Li,
Zinan Wang,
Aoxiang Liu,
Ruiyao Tao
Publication year - 2021
Publication title -
advances in materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 42
eISSN - 1687-8442
pISSN - 1687-8434
DOI - 10.1155/2021/9728248
Subject(s) - control theory (sociology) , particle swarm optimization , rotor (electric) , dynamic balance , vibration , harmonic balance , modal , helicopter rotor , nonlinear system , modal analysis , optimization problem , computer science , engineering , physics , materials science , algorithm , mechanical engineering , control (management) , quantum mechanics , artificial intelligence , polymer chemistry
The dynamic balance is a significant issue for the nonlinear dynamic characteristics of the spindle rotor system. However, there is a problem that the dynamic balance is lacking detailed study on optimization method. In the paper, a modal dynamic balance optimization model of spindle rotor system is proposed, which can intend to improve the accuracy of spindle rotor system modal dynamic balance. Because the multiorder unbalance components are the main spindle rotor system mode shapes, the particle swarm optimization (PSO) method is adopted. The sum of squares of residual vibration after balancing is taken as the optimization objective, and the correction is presented as the optimization variable in the optimization model. The optimal correction weight of every unbalance component is calculated through a modal matrix equation of PSO. The vibration amplitude that is greatly reduced after optimization balance is presented under different conditions. The balancing effect shows a better dynamic characteristic than that of traditional methods. And the fluctuation range of the axis track of the rotor system also shows reductive phenomenon. The proposed optimization spindle rotor system model is well verified through experiments. It can contribute a theoretical optimization foundation for available dynamic balance in spindle rotor system.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom