@article{ZHANG2025, 
author = {Shuai ZHANG and WeiMin WANG and WeiBo LI and JiaLe WANG and Wei WANG},
title = {Identification of rotor imbalance under anisotropic support conditions},
year = {2025},
journal = {Journal of Beijing University of Chemical Technology (Natural Science Edition)},
volume = {52},
number = {1},
pages = {103-112},
keywords = {dynamic balance of rotor, forward precession decomposition, slow rolling vector compensation, cross-correlation algorithm, least squares influence coefficient method},
url = {https://www.sciopen.com/article/10.13543/j.bhxbzr.2025.01.012},
doi = {10.13543/j.bhxbzr.2025.01.012},
abstract = {When there is a difference in the rigidity of a rotor support, the vibration vector is affected by the mounting angle of the sensor, resulting in a difference in the dynamic balancing effect. By separating the time-domain data collected by two sensors in the direction orthogonal to the measurement point, the forward and backward precession components of the rotor vibration signal can be separated based on the Hilbert transform, and the amplitude and phase of the forward component can be extracted by using the cross-correlation method, so as to realize the measurement of the rotor imbalance vector. Based on this method, different rotors have been analyzed and the results verified by numerical simulation and experimental analysis. The simulation results show that the residual vibration at the bearing support position within the balanced speed range with our new method using multi-plane and multi-speed dynamic balancing is lower than that obtained after balancing with a single-direction sensor. The experimental results for a flexible rotor indicate that after using our new method for dynamic balancing, the residual vibration at critical speed is lower than that after using a single direction sensor for dynamic balancing. The results of the rigid rotor experiment show that after using this method for dynamic balancing and removing the influence of slow rolling vector, the vibration amplitude of the test rotor measurement point mainly due to imbalance decreases by at least 54.17%, while the corresponding measurement point amplitudes at single X and single Y direction measurement points decrease by 37.50% and 33.33%, respectively, after dynamic balancing. In summary, the proposed method can improve the accuracy of dynamic balancing and should have valuable engineering applications.}
}