Error compensation of tetrahedron magnetic gradiometer

Zhen-tao, 于振涛 Yu; Jun-wei, 吕俊伟 Lv; Ning, 郭宁 Guo; Jing, 周静 Zhou

doi:10.3788/ope.20142210.2683

Cited by 4 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Gang et al [14] calibrated the magnetic gradient tensor system using a linear calibration method, but two nonlinear conversions were used to linearize the nonlinear mathematical model of single vector magnetometer calibration, and the calculation process was complicated. Zhen-tao et al [15] achieved calibration of the tetrahedron magnetic gradiometer with the restriction of traceless and symmetric properties. Calibration matrixes were estimated with a genetic algorithm; however, the optimization algorithm was easily trapped into local optimization, and the convergent speed was slow.…”

Section: Introductionmentioning

confidence: 99%

Error Calibration of Cross Magnetic Gradient Tensor System with Total Least‐Squares Method

Chi¹,

Wang²,

Tao³

et al. 2023

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The magnetic gradient tensor system configured by fluxgate magnetometers is subjected to different scale factors, three-axis nonorthogonality, bias, and misalignment errors. All those errors above will influence the measurement precision directly, so the magnetic gradient tensor system must be calibrated before use. In this paper, an error calibration method of the magnetic gradient tensor system is proposed. The procedure of the proposed method is as follows. Firstly, the error calibration model of the single fluxgate magnetometer is established and generated an ellipsoid mathematical expression. To simplify the calculation, the ellipsoid mathematical expression is transformed into a linear model of intermediate variables, and then, error parameters are estimated by the total least-squares method. Secondly, the orthogonal procrustes problem is adopted to calibrate misalignment errors. Finally, simulations and experiments with a cross magnetic gradient tensor system are carried out for verification of the proposed error calibration method. Results show that compared with the original least-squares method, the proposed method can increase the measurement accuracy of the cross magnetic gradient tensor system greatly.

show abstract

Section: Introductionmentioning

confidence: 99%

Error Calibration of Cross Magnetic Gradient Tensor System with Total Least‐Squares Method

Chi¹,

Wang²,

Tao³

et al. 2023

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

Tensor coaxial calibration of magnetic sensor array

et al. 2022

View full text Add to dashboard Cite

In order to effectively solve the influence of the magnetic sensor array error caused by axial inconsistency on the measurement accuracy, an array composed of four fluxgate sensors is built by using the Euler rotation matrix, and the consistency correction is carried out. Firstly, aiming at the non orthogonal, scale factor, zero bias and other error factors of the sensor itself, a 9-PARAMETER correction coefficient matrix is constructed to compensate the non orthogonal magnetic field measurement of the sensor, and the ideal orthogonal three component magnetic field measurement value is obtained. On the above-mentioned basis, the reference sensor in the magnetometry array is selected, and the roll, pitch and azimuth of the sensor to be calibrated are transformed to establish the Euler rotation matrix, and the model for 9-PARAMETER consistency correction is constructed. The reference sensor and the sensor to be calibrated are placed on the magnetic gradiometer for experimental verification. The experimental results show that the root mean square error of magnetic field measurement is within 10 nT after the sensor measurement error compensation correction, and the angle error of each axis measurement is within 0.01åfter the consistency correction (4.22 nT). It shows that the magnetic field measurement values of different measuring points in the sensor array can be well projected on the coordinate axis of the reference sensor after correction, and the magnetic field information of the measuring points can be correctly projected, which has high reliability.

show abstract

Impact factor analysis on precision of magnetic gradient full tensor measurement system

Zhang

Chen

et al. 2021

AIP Advances

View full text Add to dashboard Cite

In order to achieve a comprehensive analysis of the influencing factors on the accuracy of the magnetic gradient full tensor measurement system, an orthogonal experimental design method is proposed to analyze the errors caused by the influencing factors. The influence of each factor on the accuracy of the measurement system is obtained more comprehensively. Furthermore, the relative degree of influence of the factor is obtained. Four factors including resolution, baseline length, measurement distance, and magnetic moment direction are selected for simulation calculation. The simulation results and analysis show that among the selected factors, the resolution has the greatest influence on the accuracy of the measurement system and the magnetic moment direction has the least influence. In the actual measurement system design, if the optimal configuration of the four factors cannot be satisfied, the former can be satisfied in priority in the order of resolution, measurement distance, baseline length, and magnetic moment direction.

show abstract

Error compensation of tetrahedron magnetic gradiometer

Cited by 4 publications

References 0 publications

Error Calibration of Cross Magnetic Gradient Tensor System with Total Least‐Squares Method

Error Calibration of Cross Magnetic Gradient Tensor System with Total Least‐Squares Method

Tensor coaxial calibration of magnetic sensor array

Impact factor analysis on precision of magnetic gradient full tensor measurement system

Contact Info

Product

Resources

About