基于位移信号的磁悬浮飞轮转速估计

刘虎; 杨振鹏; 武登云

doi:10.3788/OPE.20202805.1116

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基于位移信号的磁悬浮飞轮转速估计

微纳技术与精密机械 | 更新时间：2020-07-09

- 基于位移信号的磁悬浮飞轮转速估计
- Estimation of rotor speed using displacement signals in magnetic suspended flywheel
- 光学精密工程 2020年28卷第5期页码：1116-1123
- 作者机构：
  
  1.北京航空航天大学仪器科学与光电工程学院, 北京100191
  2.北京航空航天大学新型惯性仪表与导航系统技术国防重点学科实验室, 北京100191
  3.北京控制工程研究所, 北京 100080
- 作者简介：
  
  [ "刘虎(1981-), 男, 河北武邑人, 讲师, 2003年, 2010年于北京航空航天大学分别获得学士、博士学位, 主要从事磁悬浮轴承的控制方法及工业应用方面的研究。E-mail：liuhu99@buaa.edu.cn" ]
  杨振鹏(1995-), 男, 江西抚州人, 硕士研究生, 2017于北京航空航天大学获得学士学位, 主要从事磁悬浮轴承主振动控制研究。E-mail:yangzp_zp@163.com YANG Zhen-peng, E-mail:yangzp_zp@163.com
- 基金信息：
  
  国家自然科学基金资助项目(61503015);国家自然科学基金资助项目(61773038);北京市自然科学基金资助项目(3182024)
- DOI：10.3788/OPE.20202805.1116
  中图分类号： V19
- 收稿日期：2019-10-31，
  
  修回日期：2019-12-05，
  
  录用日期：2019-12-5，
  
  纸质出版日期：2020-05-15
- 稿件说明：
移动端阅览
刘虎, 杨振鹏, 武登云. 基于位移信号的磁悬浮飞轮转速估计[J]. 光学精密工程, 2020,28(5):1116-1123.

hu LIU, Zhen-peng YANG, Deng-yun WU. Estimation of rotor speed using displacement signals in magnetic suspended flywheel[J]. Optics and precision engineering, 2020, 28(5): 1116-1123.
刘虎, 杨振鹏, 武登云. 基于位移信号的磁悬浮飞轮转速估计[J]. 光学精密工程, 2020,28(5):1116-1123. DOI： 10.3788/OPE.20202805.1116.

hu LIU, Zhen-peng YANG, Deng-yun WU. Estimation of rotor speed using displacement signals in magnetic suspended flywheel[J]. Optics and precision engineering, 2020, 28(5): 1116-1123. DOI： 10.3788/OPE.20202805.1116.

摘要

针对测速传感器故障情况下磁悬浮飞轮不平衡振动抑制所需的高精度的转速信息的提取

提出了一种通过预先提取转子位移信号和转速信号构建BP神经网络模型

从而通过位移信号实时估计转速的方法; 通过MATLAB/Simulink构建了磁悬浮飞轮系统模型

以仿真得到的位移和转速数据训练出一个神经网络模块

以此实时估计转速

得到恒速和变速两种情形下的转速估计结果

并与测速传感器获得的转速进行比较。仿真和实验结果证明

该转速估计方法在恒速和变速时均估计效果良好

实验估计误差不超过20 r/min。

Abstract

To acquire the high-precision rotational speed information necessary to suppress unbalanced vibration ina magnetic suspension flywheel under the circumstance of speed sensors failure

a BP neural network model was constructed by pre-extracting the rotor displacement signal and the rotational speed signal to estimate the rotational speed in real time using the displacement signal. The magnetic suspension flywheel system model was constructed using MATLAB/Simulink. A neural network module was trained using simulated displacement and rotational speed data to estimate the rotational speed in real time

and the estimation results under constant speed and variable speed were obtained and compared with the system speed acquired from the speed sensor. The simulation and experimental results show that the speed estimation method demonstrates good estimation accuracy at both constant speed and variable speed

with an estimation error of less than 20 r/min throughout the experiment.

关键词

Keywords

references

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