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Temperature error compensation method for fiber optic gyroscope based on a composite model of k-means,support vector regression and particle swarm optimization 认领 引用 被引量：1
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作者 CAO Yin LI Lijing LIANG Sheng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第2期510-522,共13页
As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely... As the core component of inertial navigation systems, fiber optic gyroscope (FOG), with technical advantages such as low power consumption, long lifespan, fast startup speed, and flexible structural design, are widely used in aerospace, unmanned driving, and other fields. However, due to the temper-ature sensitivity of optical devices, the influence of environmen-tal temperature causes errors in FOG, thereby greatly limiting their output accuracy. This work researches on machine-learn-ing based temperature error compensation techniques for FOG. Specifically, it focuses on compensating for the bias errors gen-erated in the fiber ring due to the Shupe effect. This work pro-poses a composite model based on k-means clustering, sup-port vector regression, and particle swarm optimization algo-rithms. And it significantly reduced redundancy within the sam-ples by adopting the interval sequence sample. Moreover, met-rics such as root mean square error (RMSE), mean absolute error (MAE), bias stability, and Allan variance, are selected to evaluate the model’s performance and compensation effective-ness. This work effectively enhances the consistency between data and models across different temperature ranges and tem-perature gradients, improving the bias stability of the FOG from 0.022 °/h to 0.006 °/h. Compared to the existing methods utiliz-ing a single machine learning model, the proposed method increases the bias stability of the compensated FOG from 57.11% to 71.98%, and enhances the suppression of rate ramp noise coefficient from 2.29% to 14.83%. This work improves the accuracy of FOG after compensation, providing theoretical guid-ance and technical references for sensors error compensation work in other fields. 展开更多
关键词 fiber optic gyroscope(FOG) temperature error com-pensation composite model machine learning clustering regression.
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Suppression of the vapor cell temperature error in a spin-exchange relaxation-free comagnetometer 认领 引用
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作者 Jia-Li Liu Li-Wei Jiang +2 位作者 Chi Fang Xin Zhao Yuan-Qiang Chen 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第12期236-241,共6页
The fluctuation of the vapor cell temperature leads to the variations of the density of the alkali metal atoms,which seriously damages the long-term stability of the spin-exchange relaxation-free(SERF)comagnetometer.T... The fluctuation of the vapor cell temperature leads to the variations of the density of the alkali metal atoms,which seriously damages the long-term stability of the spin-exchange relaxation-free(SERF)comagnetometer.To address this problem,we propose a novel method for suppressing the cell temperature error by manipulating the probe laser frequency.A temperature coefficient model of the SERF comagnetometer is established based on the steady-state response,which indicates that the comagnetometer can be tuned to a working point where the output signal is insensitive to the cell temperature fluctuation,and the working point is determined by the relaxation rate of the alkali metal atoms.The method is verified in a K-Rb-21Ne comagnetometer,and the experimental results are consistent with the theory.The theory and method presented here lay a foundation for the practical applications of the SERF comagnetometer. 展开更多
关键词 spin-exchange relaxation-free atomic comagnetometer cell temperature error probe laser frequency
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Temperature compensation method for static level monitoring system and its application 认领 引用
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作者 Mingyu Lei Yanliang Li +8 位作者 Qing Yang Dian Xiao Jialiang Liu Fei Lv Jisheng Sui Lianchong Li Tianhui Ma Guanwen Cheng Dingzhu Liu 《Railway Sciences》 2025年第4期536-549,共14页
Purpose–This study solves the key problem that the static level monitoring is susceptible to temperature interference and affects the accuracy in slope instability/deformation monitoring.The purpose is to develop a r... Purpose–This study solves the key problem that the static level monitoring is susceptible to temperature interference and affects the accuracy in slope instability/deformation monitoring.The purpose is to develop a reliable temperature compensation method for the system,improve the accuracy of slope stability monitoring and provide support for improving the safety and safety monitoring of engineering spoil slope and other projects.Design/methodology/approach–Combined with theoretical analysis and experimental verification,the temperature compensation method is explored.The working principle of the hydrostatic leveling monitoring system is analyzed and the data processing formula,the temperature error calculation formula and the calculation formula for eliminating the error settlement value are derived.The temperature compensation method is established and verified by the field test of the engineering spoil slope which is disturbed by a debris flow.Findings–The experimental results show that this method can reduce the error of the static level monitoring system by about 40%.The field test shows that the fluctuation of slope settlement monitoring value is reduced after temperature compensation and the monitoring value is consistent with the actual situation,which has certain practicability.Originality/value–The originality of this study is to derive a theoretical formula for quantifying/eliminating temperature errors in static leveling and to establish a practical temperature compensation method.The accuracy of the system is improved,which provides a reference for slope stability monitoring under complex environment(especially railway geotechnical engineering)and promotes the development of precision monitoring technology. 展开更多
关键词 Engineering spoil Slope instability Static level Temperature error Model correction
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Data processing and error analysis for the CE-1 Lunar microwave radiometer 认领 引用 被引量：1
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作者 Jian-Qing Feng Yan Su +2 位作者 Jian-Jun Liu Yong-Liao Zou Chun-Lai Li 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2013年第3期359-372,共14页
The microwave radiometer （MRM） onboard the Chang＇ E-1 （CE-I） lu- nar orbiter is a 4-frequency microwave radiometer, and it is mainly used to obtain the brightness temperature （TB） of the lunar surface, from whi... The microwave radiometer （MRM） onboard the Chang＇ E-1 （CE-I） lu- nar orbiter is a 4-frequency microwave radiometer, and it is mainly used to obtain the brightness temperature （TB） of the lunar surface, from which the thickness, temperature, dielectric constant and other related properties of the lunar regolith can be derived. The working mode of the CE-1 MRM, the ground calibration （including the official calibration coefficients）, as well as the acquisition and processing of the raw data are introduced. Our data analysis shows that TB increases with increasing frequency, decreases towards the lunar poles and is significantly affected by solar illumination. Our analysis also reveals that the main uncertainty in TB comes from ground calibration. 展开更多
关键词 space vehicles -- instruments： microwave radiometer -- Moon： bright-ness temperature -- method： data processing -- error analysis
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Effect of Thermal Radiation Heat Transfer on the Temperature Measurement by the Thermocouple in Premixed Laminar Flames 认领 引用 被引量：5
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作者 JIN Kairu TIAN Zhenyu 《Journal of Thermal Science》 SCIE EI CAS CSCD 2022年第2期541-551,共11页
In the past 30 years,the effect of thermal radiation and convection heat transfer,which are predominant at high temperature and can affect the measurement accuracy of thermocouple,were not fully considered in the fiel... In the past 30 years,the effect of thermal radiation and convection heat transfer,which are predominant at high temperature and can affect the measurement accuracy of thermocouple,were not fully considered in the field of laminar flame researches.In this work,the effect of thermal radiation heat transfer was newly calculated by determining the spectral irradiation heat flux from the whole space to thermocouple and the radiation heat loss from thermocouple junction to surroundings.Analysis reveals that the thermocouple itself maintains at high temperature,resulting serious thermal radiation heat loss,which can be compensated via receiving energy from convection-transferred heat as well as thermal radiation emitted by flame and burner surface.Such method was applied to correct the temperatures measured by thermocouple in rich nitromethane flame as reference.The results indicate that the radiation heat loss plays a dominant role,while the radiations emitted by flame and burner surface account for minor contribution with the percentage of 20.78%at the height above burner(HAB)of 0.4 mm,3.63%at HAB of 2.0 mm and even smaller at higher HAB.Temperature correction states that the maximum temperature error is 117.60 K,where the effect of thermal radiation emitted by flame and burner surface is less than 1.75 K.Consequently,it is provably reasonable and feasible to concentrate on the radiation heat loss and ignore the effect of thermal radiation emitted by flame and burner in real combustion processes. 展开更多
关键词 thermal radiation heat transfer temperature error premixed laminar flame
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Aerosol as a critical factor causing forecast biases of air temperature in global numerical weather prediction models 认领 引用 被引量：6
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作者 Xin Huang Aijun Ding 《Science Bulletin》 SCIE EI CAS CSCD 2021年第18期1917-1924,M0004,共8页
Weather prediction is essential to the daily life of human beings.Current numerical weather prediction models such as the Global Forecast System(GFS)are still subject to substantial forecast biases and rarely consider... Weather prediction is essential to the daily life of human beings.Current numerical weather prediction models such as the Global Forecast System(GFS)are still subject to substantial forecast biases and rarely consider the impact of atmospheric aerosol,despite the consensus that aerosol is one of the most important sources of uncertainty in the climate system.Here we demonstrate that atmospheric aerosol is one of the important drivers biasing daily temperature prediction.By comparing observations and the GFS prediction,we find that the monthly-averaged bias in the 24-h temperature forecast varies between±1.5℃in regions influenced by atmospheric aerosol.The biases depend on the properties of aerosol,the underlying land surface,and aerosol–cloud interactions over oceans.It is also revealed that forecast errors are rapidly magnified over time in regions featuring high aerosol loadings.Our study provides direct‘‘observational"evidence of aerosol’s impacts on daily weather forecast,and bridges the gaps between the weather forecast and climate science regarding the understanding of the impact of atmospheric aerosol. 展开更多
关键词 Weather prediction Atmospheric aerosol Temperature forecast errors Aerosol-radiation interactions Aerosol-cloud interactions
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