Temperature Error Compensation Research Articles

Temperature error compensation method of fiber optic gyroscope based on deep learning

This work provides an error compensation strategy based on deep learning to address the temperature error of a fiber optic gyroscope (FOG). The Attention structure was used to improve the Long Short-Term Memory Network (LSTM), and the improved network was utilized to establish the prediction and compensation model of FOG error. From the two perspectives of the learning ability of the neural network and the improvement of FOG performance, this paper selects three indicators: prediction accuracy, mean square error, and FOG bias stability to comprehensively evaluate the performance of the compensation model. Through comparison, the compensation effect is significantly enhanced.

Research On High Precision Fiber Optic Platform System Temperature Compensation Technology

In a high-precision fiber optic platform system, temperature changes will have a significant impact on the start-up speed and actual application accuracy. In order to effectively improve the navigation accuracy of the system, the article analyzes the temperature characteristics of the system-level calibration error parameters and establishes a temperature error model. Finally, a temperature compensation test and a platform model calibration test are designed to verify the compensation effect. The test results show that the established temperature error compensation model is accurate and effective. The stability of error parameters has increased by an order of magnitude. The method improves the performance of the fiber optic platform at the start-up stage, and has a small amount of calculation, which has high engineering application value.

Determination and algorithmic compensation of the temperature errors of the navigation triaxial linear accelerometer

The method of experimental determination in the production conditions of the temperature coefficients of the mathematical model of temperature errors of the navigation triaxial linear accelerometer (AT) with the help of a tilter during a single passage of all calibration temperatures is considered. For the polynomial and piecewise linear models of temperature errors of the triaxial accelerometer, mathematical models for identifying the temperature coefficients of these errors were obtained. Ways of algorithmic compensation of temperature errors of AT in the composition of the product using two methods are proposed.
 Adequacy of the developed method of determining the temperature coefficients of AT has been experimentally confirmed. It is shown that the algorithmic compensation of temperature errors of AT by both methods gives approximately the same result - a reduction of temperature errors of AT by 3-4 times. If it is necessary to increase the accuracy of this compensation, it is necessary to use more complex models of temperature errors of AT.

Optimal design and implementation of tunnelling magnetoresistance based small current sensor with temperature compensation

This paper proposes a tunnelling magnetoresistance (TMR) based current sensor considering temperature error compensation, for the measurement of current in the range from a few hundred micro-amperes to a few hundred mini-amperes, in the applications in power systems. Theoretic and simulation analysis are studied for the optimization design of the TMR based small current sensor in the perspective of the magnetic loop structure, magnetic core parameters, and secondary circuit. An improved temperature error compensation circuit is proposed to suppress the sensitivity drift of the sensor. A prototype is built to verify the proposed design. According to the experiment results, the proposed TMR small current sensor has a measurement range of ±200 mA and a sensitivity of 10 V/A. The temperature error compensation scheme can reduce the temperature coefficient of sensitivity of the sensor from 1780 ppm/°C to 504 ppm/°C. The proposed TMR small current sensor can measure small current effectively.

A method for temperature error compensation in fiber-optic gyroscope based on machine learning

This work presents a machine-learning based method for temperature error compensation of fiber optic gyroscope (FOG). Alternative to existing methods for constructing samples by single data point, a novel method of constructing samples by sequence is proposed, which fully considers the hysteresis and delay of temperature error. Moreover, temperature experiments with three distinct temperature trends, i.e., heating, holding and cooling, are conducted. Following the construction of training and test sets, the relevant training and test processes are completed using SVR algorithm. According to the degree of approximation in predicted value relative to the real value and the degree of improvement in gyro stability, the effects of various sample construction methods on the corresponding error compensation are analyzed. Considering the root mean square error (RMSE), mean absolute value error (MAE) and improvement-factor of FOG zero-bias stability as measurement indicators, this work proposes to construct samples by sequence with temperature trend feature-extraction, which effectively improves the overall accuracy of gyroscope. Allan variance is also utilized to verify the effectiveness of our proposed method. Lastly, this study also provides a theoretical guidance and reference for temperature error compensation in other types of sensors.

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C.

Research on temperature error compensation method of vehicle-mounted laser gyro SINS

In order to solve the problem that the measurement accuracy of vehicle-mounted laser gyro strapdown inertial navigation system (SINS) is affected by the temperature change, a temperature error compensation method which can adapt to the full temperature environment is proposed. Based on the phenomenon that the temperature of the inertial sensor is still rising when the temperature of the temperature control box is kept, a continuous temperature change experiment is designed. Then, Pearson correlation analysis of the output of laser gyro and quartz flexible accelerometer with temperature, temperature rate and temperature gradient has been carried out. Based on that, the temperature error models of gyro and accelerometer are constructed, and the temperature compensation method based on polynomial model is proposed. The results show that this method could compensate the temperature error of the laser gyro and the quartz flexible accelerometer effectively, and the zero-bias stability of them are both improved, especially the zero-bias stability of the accelerometer is improved by at least one order of magnitude, the accuracy of inertial measurement in full temperature environment is improved effectively.

In-situ variable reflectance spectra model of two-dimensional material prepared by CVD

Here we introduce the spectral measurement model of online reflectance spectra aimed at the variable temperature environment. The model combines the traditional differential reflectance spectroscopy (DRS) model with the temperature error compensation method. The blank experiments and molybdenum disulfide (MoS2) growth experiment prepared by chemical vapor deposition (CVD) were monitored in situ by using the new DRS model proposed in this work. The characteristic peaks of MoS2 at 1.82 eV and 1.99 eV were successfully discovered in the spectra processed by the temperature error compensation method. This observation reveals that MoS2 thin films have grown. The morphology and Raman properties of MoS2 domains were off-line characterized using optical microscopy and Raman spectroscopy. The experimental results indicate that the spectral model and the temperature error compensation method can contribute to the real-time growth characterization of two-dimensional material (2D). It is of great significance for the preparation and application of 2D materials.

Erratum to: Precision Control of the 6-DOF Parallel Kinematic Mechanism of Space Application Based on Compensation of Kinematic and Temperature Errors

Erratum to: Precision Control of the 6-DOF Parallel Kinematic Mechanism of Space Application Based on Compensation of Kinematic and Temperature Errors

Precision Control of the 6-DOF Parallel Kinematic Mechanism of Space Application Based on Compensation of Kinematic and Temperature Errors

The paper introduces the ways to improve the control accuracy of the parallel kinematic mechanisms of space application. The sources of errors in positioning and orientation of the mechanism developed are given. The ways are suggested for compensating the kinematic and temperature errors of linear drives and mechanism members.

Modelling and compensation of temperature errors for articulated arm coordinate measuring machines

The temperature variation is an important factor affecting the accuracy of the articulated arm coordinate measuring machine (AACMM). This paper addresses the modelling and compensation of temperature errors in AACMMs. Firstly, a temperature field model of AACMMs is established by finite element analysis, based on which the influence of temperature change on single-point repeatability accuracy and spatial distance measuring accuracy for AACMMs are analysed. The results of the analysis show that non-zero linear parameters of AACMMs are influenced by temperature variation greatly, while the angular parameters are almost unchanged. Then, a temperature scaling method is proposed to improve the distance measuring accuracy of AACMMs, and a linear regression temperature error compensation model is established under the simulation environment. Experimental results show that in the presence of temperature scaling method, the average absolute value of distance measuring accuracy is improved by 65.24%.

Modelling and compensation of temperature errors for articulated arm coordinate measuring machines

Modelling and compensation of temperature errors for articulated arm coordinate measuring machines

Compensation of temperature errors in pressure piezoconverters

Measuring pressure converters are one of the most popular control devices in technological processes. The most additional common error is temperature error. One of the causes of the additional temperature error is the uneven temperature field on the pressure converter measuring membrane surface that is determined by the nature of temperature impact. Constructive methods for reducing the stated error lie also in finding the topology of a resistance strain gage on the converter membrane that ensures minimum sensitivity to the uneven temperature field while retaining the pressure sensitivity. The effectiveness check of various topologies is hindered by different technical, technological and economic problems. The article proposes to run a check of topological solutions with the help of a mathematical model of the membrane temperature field that takes into account the temperature impact on the converter. The exponential function was chosen as a modelling function because it corresponded to the experimentally obtained temperature distribution data. This function allows virtually forming temperature field distributions on the membrane surface, characteristic of static, dynamic (thermal shock) and targeted temperature impact. This model will allow assessing without a physical experiment of additional temperature errors of various topological solutions. Additional temperature errors of the classic four resistance element topology and the topology proposed by the authors with component resistance strain gages are analysed as examples. The potential of topological solutions in minimization of additional temperature errors in pressure converters is shown. The approach set forth in the article streamlines the search for constructive solutions for minimizing additional temperature errors in pressure converters by reducing physical simulation stage.

IR-Band Conversion of Target and Background Using Surface Temperature Estimation and Error Compensation for Military IR Sensor Simulation.

Military infrared (IR) imaging systems utilize one or more IR wavelength-bands, among short wavelength IR (SWIR), middle wavelength IR (MWIR), and long wavelength IR (LWIR) band. The IR image wavelength-band conversion which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image is needed for IR signature modeling and image synthesis in the IR systems. However, the IR wavelength-band conversion is very challenging because absorptivity and transmittance of objects and background (atmosphere) are different according to the IR wavelength band and because radiation and reflectance characteristics of the SWIR are very different from the LWIR and MWIR. Therefore, the IR wavelength-band conversion in this paper applies to only IR targets and monotonous backgrounds at a long distance for military purposes. This paper proposes an IR wavelength-band conversion method which transforms one arbitrary IR wavelength-band image to another IR wavelength-band image by using the surface temperature estimation of an object and the error attenuation method for the estimated temperature. The surface temperature of the object is estimated by an approximated Planck’s radiation equation and the error of estimated temperature is corrected by using the slope information of exact radiance along with the approximated one. The corrected surface temperature is used for generating another IR wavelength-band image. The verification of the proposed method is demonstrated through the simulations using actual IR images obtained by thermal equipment.

TEMPERATURE CALIBRATION OF NAVIGATIONAL ACCELEROMETER UNIT

Temperature calibration method of navigational accelerometer unit, which excludes accelerometer unit reset in temperatures and allows performing calibration by one-time passage at all calibration temperatures, is considered. Special device – tilt, is used for accelerometer unit setting in test positions. Model of absolute instrumental measurement error of accelerometer unit acceleration projections in measurement axes was obtained by known accelerometer unit metrology models. Polynomial and piecewise linear model of accelerometer unit temperature errors were obtained using appropriate expressions for two types of dependencies twelve passport constants of temperature change. In addition, simplified polynomial and piecewise linear models of accelerometer unit temperature errors were obtained. Two methods of algorithmic compensation of accelerometer unit temperature errors are proposed: method 1 -mathematical method of correction accelerometer unit metrology model passport constants current values based on current temperature, method 2 - method of introducing amendments to accelerometer unit measurement results, values of which are equal to temperature errors values. Experimentally temperature calibration of accelerometer unit using tilt was performed and its quality was checked, which performed by comparing measurement errors of gravity acceleration module at verification temperatures. Adequacy of the developed method of navigational accelerometer unit temperature calibration was confirmed. Two methods of temperature errors accelerometer unit algorithmic compensation were compared, each method gave almost the same result - reducing accelerometer unit temperature errors by three-four times. For increasing compensation accuracy it is recommended to use complex accelerometer unit temperature errors models and, or increase number of piecewise linear model subbands and polynomial model order.

Temperature characteristics and error compensation for quartz flexible accelerometer

Reduction of error due to the influence of temperature on the quartz flexible accelerometer without any heating device is a difficult task, and is also a tendency for research and application. In this paper, static and dynamic temperature compensation models are established in order to reduce the temperature influence on accelerometer measurement accuracy. Combined with the experiment data, the relationship between the accelerometer output accuracy, temperature and the magnitude of acceleration is analyzed. The data collected from the temperature experiment show that output value of the accelerometer varies with temperature. The method of uniaxial quadrature experiment is adopted and the accelerometer output value is gauged at temperature ranging from ?20°C to 50°C. Having used the static and the dynamic temperature compensation models, the accelerometer temperature error compensation experiment is conducted and the compensated errors by the two models are analyzed. The result shows that the compensated value meets the technical requirements. Two technical indicators, the zero bias K0 and the scaling factor K1, which are used to measure the degree of accelerometers, are both improved and their fluctuation ranges are reduced.

Temperature Error Compensation in Two-Component Microelectromechanical Gyroscope

This paper presents the design and simulation of a microelectromechanical gyroscope that simultaneously determines two components of angular velocity. In this device, the silicon sensor is started by an electrostatic actuator to perform a linear harmonic motion at a controlled speed. The movable masses of the sensor move in two directions, orthogonal to the primary vibrations of the sensor under the action of Coriolis forces. This paper considers how temperature influences eigenfrequencies and informative vibrational magnitudes of the micromechanical angular velocity sensor. The parameters that have the greatest impact on the sensor output behavior are determined by a finite-element analysis method. Techniques to stabilize vibration eigenfrequencies of the sensing element are suggested.

A Nonlinear Multiparameters Temperature Error Modeling and Compensation of POS Applied in Airborne Remote Sensing System

The position and orientation system (POS) is a key equipment for airborne remote sensing systems, which provides high-precision position, velocity, and attitude information for various imaging payloads. Temperature error is the main source that affects the precision of POS. Traditional temperature error model is single temperature parameter linear function, which is not sufficient for the higher accuracy requirement of POS. The traditional compensation method based on neural network faces great problem in the repeatability error under different temperature conditions. In order to improve the precision and generalization ability of the temperature error compensation for POS, a nonlinear multiparameters temperature error modeling and compensation method based on Bayesian regularization neural network was proposed. The temperature error of POS was analyzed and a nonlinear multiparameters model was established. Bayesian regularization method was used as the evaluation criterion, which further optimized the coefficients of the temperature error. The experimental results show that the proposed method can improve temperature environmental adaptability and precision. The developed POS had been successfully applied in airborne TSMFTIS remote sensing system for the first time, which improved the accuracy of the reconstructed spectrum by 47.99%.

The Novel Model of Fusion Temperature Error Compensation System by Neural Network and Smart Sensors

Neural network is a non-linear statistical data modeling tool, commonly used for input and output of the complex relationships between modeling, or used to explore the patterns in the data. In this paper, the data fusion theory and neural network method is applied to the smart sensor error compensation, greatly improving the magnetic flux leakage testing sensor stability and accuracy. Here the intelligent sensor information fusion is applied to the error compensation. The detection device sensor components to add a temperature sensor is real-time record of working environment temperature. The paper proposes the novel model of fusion temperature error compensation system by neural network and smart sensors. Finally the experiments verify the validity of the method.

Velocity Temperature Characteristics of Time Domain Reflectometry Cable Length Measurement System

Traveling wave velocity is the key to the measuring accuracy of the time-domain reflectometry cable length measurement system. The velocity value is affected by many factors. In order to reduce the ambient temperature impact on velocity, the velocity temperature characteristics of time domain reflectometry cable length measurement system are studied. The change law of the traveling wave propagation velocity in the cable with the change in ambient temperature is studied. The velocity temperature error compensation coefficients of traveling wave in the PVC insulated cable is obtained according to the experimental data by measuring the traveling wave velocity in these cables at different temperature. Experimental results show that the measuring accuracy of the time-domain reflectometry cable length measurement system is improved significantly by velocity temperature compensation.