Effect of Random Error of Temperature Sensors on the Quality of Temperature Compensation of FOG Bias by a Neural Network

Klimkovich, B. V.

doi:10.1134/s2075108721010089

Cited by 7 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data transmission is divided into forward propagation and back propagation. The back propagation carries out network learning by constantly modifying the weight and threshold (Klimkovich, 2021;Chen, 2022). This structure can ensure that the network can realise active learning and has the ability of nonlinear classification.…”

Section: Radial Basis Function Neural Networkmentioning

confidence: 99%

“…At present, the commonly used error modelling methods of laser gyro include time series method, wavelet network, neural network and so on. At the same time, the temperature error model in the temperature compensation method of laser gyroscope can effectively realise the real-time temperature compensation of laser gyroscope (Klimkovich, 2021;Chen, 2022;Fang et al, 2020). In view of this, a neural network oriented zero deviation compensation model of laser gyroscope is proposed and compared with the improved model, in order to improve the temperature compensation effect of laser gyroscope in China.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Zero-bias error compensation method of laser gyro based on neural network

Cui¹,

Cong²

2023

IJWMC

View full text Add to dashboard Cite

Aiming at the problem that the accuracy of the current compensation model for laser gyro bias error is low, an improved RBFNN bias error compensation model of laser gyro is proposed. The standardisation constant and data centre of the original data are obtained through the self-organising feature mapping network. The sample centre of the new sample data is obtained by the fastest decline of the expected variance of OLS algorithm. The results show, the improved RBF neural network algorithm has the best performance. under normal temperature, temperature change rate of 1C/min and temperature change rate of 3C/min, the zero-bias range of laser gyro is 3.491-3.508C/h, 3.992-4.021C/h and 4.092-4.123C/h, respectively. The research results provide new reference suggestions for the zero bias temperature compensation scheme of laser gyro at different temperatures.

show abstract

Section: Radial Basis Function Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Zero-bias error compensation method of laser gyro based on neural network

Cui¹,

Cong²

2023

IJWMC

View full text Add to dashboard Cite

show abstract

Suppression of effects of temperature variation by high-order frequency modulation in large fiber-optic gyroscopes

Chen

Cao

Zhu

et al. 2023

Applied Physics Letters

View full text Add to dashboard Cite

Temperature variation degrades the performance of fiber-optic gyroscopes. In terms of a noise mechanism, we report that thermal phase noise contributes to the dominant effect of temperature variation in large fiber-optic gyroscopes when the conventional Shupe effect is basically suppressed. High-order frequency modulation is introduced to reduce the corresponding effect of temperature variation. A time-varying temperature variation experiment has been carried out for verification. Compared with the conventional eigen frequency modulation, the temperature sensitivity is reduced by 32 times, which effectively enhances the temperature adaptability of the fiber-optic gyroscope.

show abstract

Dual-polarization interferometric fiber optic gyroscope with Shupe effect compensation

Cao

Zhu

Shi

et al. 2023

Applied Physics Letters

View full text Add to dashboard Cite

Dual-polarization (DP) interferometric fiber optic gyroscope (IFOG) has been studied for over a decade, which has important applications in inertial navigation and rotational seismology. Currently, the Shupe effect is an important factor degrading the accuracy of the DP IFOG. Here, a dual-quadrupolar winding pattern is proposed to compensate for the Shupe effect. The finite-element simulation experiments verify that the phase shifts induced by the Shupe effect in two polarizations are almost reversed and well compensated. Static laboratory test results show that, in this configuration, the angle random walk is reduced 10-fold to 7.1×10−5 °/h, while the bias instability is reduced ninefold to 1.7×10−4 °/h. Moreover, a 3-h temperature variation experiment is carried out. The results show that, compared with the original output, the net rotation rate errors originating from the Shupe effect are effectively compensated and the temperature drift is reduced by 13 times. To summarize, the dual-quadrupolar-wound method is a valid approach to compensate for the Shupe effect, and the temperature adaptability of this DP configuration is greatly enhanced.

show abstract

Effect of Random Error of Temperature Sensors on the Quality of Temperature Compensation of FOG Bias by a Neural Network

Cited by 7 publications

References 19 publications

Zero-bias error compensation method of laser gyro based on neural network

Zero-bias error compensation method of laser gyro based on neural network

Suppression of effects of temperature variation by high-order frequency modulation in large fiber-optic gyroscopes

Dual-polarization interferometric fiber optic gyroscope with Shupe effect compensation

Contact Info

Product

Resources

About