Pose error identification algorithm based on hemispherical resonant gyroscope assembly capacitance uniformity. (July 2022)

• Record Type: Journal Article
• Authors: Yu, H.; Jin, X.; Liu, X.H.; Liu, D.P.; Li, Z.X.; Li, S.L.; J., Duan; Zhang, J.C.; Li, C.J.
• Is Part Of: Measurement. Volume 198(2022)
• Publication Date: 2022-07
• Subjects: Hemispherical resonator gyroscope -- Precision assembly -- Capacitance uniformity -- Model of pose-capacitance -- BP neural network; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111426
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A novel algorithm was proposed to guide the adjustment of spatial pose, improving capacitance uniformity of HRG; The effect of spatial poses on capacitance was discussed; A method for predicting the pose of resonator based on BP neural network was proposed. Abstract: 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.