@article{SUN2023, 
author = {Haobo SUN and Kaiming YANG and Yu ZHU and Sen LU},
title = {Modal parameter estimates for a magnetic levitation planar motor based on density clustering},
year = {2023},
journal = {Journal of Tsinghua University (Science and Technology)},
volume = {63},
number = {1},
pages = {33-43},
keywords = {magnetic levitation planar motor, density clustering, modal parameter estimates},
url = {https://www.sciopen.com/article/10.16511/j.cnki.qhdxxb.2022.21.027},
doi = {10.16511/j.cnki.qhdxxb.2022.21.027},
abstract = {Lightweight designs are needed for high acceleration and deceleration rates of a magnetic levitation planar motor (MLPM), but lightweight designs also lead to unacceptable vibrations in the MLPM. Accurate estimates of the MLPM modal parameters are the key to suppressing the vibrations. This paper presents a modal parameter estimation method based on density clustering. The system parametric frequency response function is obtained using a two-step iterative identification algorithm. Then, the DBSCAN algorithm is used for the modal analysis to remove the unstable mathematical modes. The outliers of the physical modes are also removed based on a normal distribution to obtain the final modal parameters. Simulations and tests show that this method can accurately estimate the system modal parameters.}
}