.png){kind=icon}
返回
Pose error identification algorithm based on hemispherical resonant gyroscope assembly capacitance uniformity
.png){kind=icon}
PRE
AI
DOI：10.1016/j.measurement.2022.111426.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The assembly performance of hemispherical resonant gyroscope (HRG) is directly affected by the spatial pose of the resonator and the electrode carrier, which can be reflected in the capacitance uniformity. This paper proposed a fast identification algorithm for pose error based on HRG assembly capacitance uniformity. A forward mathematical model for calculating capacitance from the resonator's pose was established and verified by experiments and simulations. The effect of pose on the capacitance was analyzed by using the mathematical model. Based on the data of pose and capacitance obtained from the mathematical model, the capacitance-pose inverse model was constructed by back propagation (BP) neural network. This novel algorithm provides a swift way to identify the pose error of resonator and achieves capacitance uniformity in HRG assembly, which can significantly improve the assembly quality and efficiency of HRG.
Keyword:
Hemispherical resonator gyroscope
Precision assembly
Capacitance uniformity
Model of pose-capacitance
BP neural network
期刊
IF:
5.6
论文数:
2.0W
被引数:
5.4W
机构
引用论文
分享收藏Stitching interferometric characterization of geometric errors of hemispherical shells.png)
MEASUREMENT
MEASUREMENTIF5.6
PREAI
分享收藏Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithmJOURNAL OF HYDROLOGY
OAAI
JOURNAL OF HYDROLOGYIF6.3
OAAI分享收藏
查看更多内容