Temperature compensation for quartz flexible accelerometer based on nonlinear auto-regressive improved model

Temperature variation is an important factor affecting the performance of Quartz flexible accelerometer (QFA). Performance deterioration of QFA degrades the navigation accuracy of inertial navigation system (INS). Normally dramatic change in temperature causes both thermal effect and severe creep ef...

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Bibliographic Details
Published in:Measurement and control (London) 2023-01, Vol.56 (1-2), p.124-132
Main Authors: Wang, Xin, Zhang, Chunxi, Song, Lailiang, Ran, Longjun, Xiao, Tingyu
Format: Article
Language:English
Subjects:
Accelerometers
Autoregressive models
Changing environments
Deformation effects
Errors
Inertial navigation
Navigation systems
Performance degradation
Performance enhancement
Quartz
Temperature compensation
Temperature control
Temperature effects
Wavelet transforms
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Summary:Temperature variation is an important factor affecting the performance of Quartz flexible accelerometer (QFA). Performance deterioration of QFA degrades the navigation accuracy of inertial navigation system (INS). Normally dramatic change in temperature causes both thermal effect and severe creep effect on the performance of QFA. Previous papers have proved that part of errors caused by thermal effect can be restrained through simple temperature compensation. However, error caused by severe creep effect is seldom considered. In this paper, creep effect and thermal effect in QFA are detailed analyzed, respectively. Furthermore, based on the analysis of thermal effect and creep effect, the novel temperature model based on nonlinear auto-regressive with external input (NARX) improved by wavelet transform (WT) is proposed to address the retardation problem caused by thermal effect. Creep error causing the ruleless deformation of QFA’s structure is separated from overall errors, and only the thermal error whose effect has strong relationship with temperature is compensated by proposed model. Moreover, a 4-point dumpling experiment in temperature control oven is conducted to train and verify the proposed temperature model. The result of the comparative experiments shows that the performance of proposed method is the best among the comparative models. The compensation result based on proposed method improves stability of 1 g output from 776 to 14.6 µg. The proposed temperature compensation method improves the performance of QFA effectively and feasibly, which could be promoted to other applications of INS in temperature changing environment.
ISSN:0020-2940
2051-8730
DOI:10.1177/00202940221089264