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清华大学学报(自然科学版)  2023, Vol. 63 Issue (1): 33-43    DOI: 10.16511/j.cnki.qhdxxb.2022.21.027
  机械工程 本期目录 | 过刊浏览 | 高级检索 |
基于密度聚类的磁悬浮平面电机模态参数估计
孙浩博, 杨开明, 朱煜, 鲁森
清华大学 精密超精密制造装备及控制北京市重点实验室, 北京 100084
Modal parameter estimates for a magnetic levitation planar motor based on density clustering
SUN Haobo, YANG Kaiming, ZHU Yu, LU Sen
Beijing Key Laboratory of Precision/Ultra-Precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China
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摘要 磁悬浮平面电机的高加减速运动需要轻量化设计,但轻量化设计也会导致磁悬浮平面电机出现不可接受的振动。对磁悬浮平面电机模态参数的准确估计是抑制振动的关键环节。该文提出了一种基于密度聚类的模态参数估计方法。首先利用两步迭代的系统辨识算法,得到系统的参数化频率响应函数;然后利用基于密度的有噪声空间聚类(DBSCAN)算法对系统进行模态分析,去除不稳定的数学模态点,并对物理模态点进行基于正态分布的离群点剔除,以获取最终的模态参数。仿真和试验表明,所提方法可以实现系统模态参数的准确估计。
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孙浩博
杨开明
朱煜
鲁森
关键词 磁悬浮平面电机密度聚类模态参数估计    
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.
Key wordsmagnetic levitation planar motor    density clustering    modal parameter estimates
收稿日期: 2022-04-13      出版日期: 2023-01-11
基金资助:杨开明,副研究员,E-mail:yangkm@tsinghua.edu.cn
引用本文:   
孙浩博, 杨开明, 朱煜, 鲁森. 基于密度聚类的磁悬浮平面电机模态参数估计[J]. 清华大学学报(自然科学版), 2023, 63(1): 33-43.
SUN Haobo, YANG Kaiming, ZHU Yu, LU Sen. Modal parameter estimates for a magnetic levitation planar motor based on density clustering. Journal of Tsinghua University(Science and Technology), 2023, 63(1): 33-43.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2022.21.027  或          http://jst.tsinghuajournals.com/CN/Y2023/V63/I1/33
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
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