A novel transient balancing technology of the rotor system based on multi modal analysis and feature points selection. (13th October 2021)

• Record Type: Journal Article
• Authors: Zhao, Shibo; Ren, Xingmin; Deng, Wangqun; Lu, Kuan; Yang, Yongfeng; Li, Lihui; Fu, Chao
• Is Part Of: Journal of sound and vibration. Volume 510(2021)
• Publication Date: 2021-10-13
• Subjects: Unbalance -- Transient balancing -- Rotor dynamics -- Modal analysis; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2021.116321
• Languages: English
• ISSNs: 0022-460X

Abstract

Highlights: The rotor dynamic balancing method based on multi modal analysis is proposed. This method identifies unbalance parameters of the rotor system in transient process. This method is robust and has the aspect of balancing without trail weights. Abstract: In this paper, a novel transient balancing technology for identifying the unbalance parameters of the rotor system is proposed. Through basic coordinate transformation and multi modal analysis of the dynamical equations of rotor system, the calculation method for transient excitation forces is proposed. The transient excitation forces are calculated by the transient responses and modal parameters at several special positions of the rotor model. Then the "feature points" are introduced in the identification procedure and the unbalance parameters are identified by selecting the "feature points" of the calculated excitation forces. The accuracy of the proposed method is demonstrated by numerical simulations and experiments of the rotor system. Identified results of the proposed method are presented for different unbalance parameters and rotor models. Effects of different random noise levels to the displacement signals, varieties in damping and support stiffness are also presented to verify the adaptability and efficiency of the proposed method. The results show that the unbalance parameters estimations are robust with respect to the above influence factors.