1. Parameter Optimization for the Induction Magnetometer of 10 kHz to 100 kHz
- Author
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Wenbin Li, Pu Huang, Zhongyi Ding, and Yuedong Xie
- Subjects
Induction magnetometers ,three-dimensional finite element simulation model ,orthogonal experiment ,response surface method ,loss analysis ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
The induction magnetometers are widely applied for magnetotelluric detection due to the characteristics of wide frequency band, large detection depth range and small size. However, the key part of the induction magnetometers – the magnetic core has eddy current loss and hysteresis loss, which significantly affects the sensitivity of the induction magnetometers. In order to improve the sensitivity of the induction magnetometers at high frequencies, this paper investigates various parameters related to the performance of the induction magnetometers working at 10 kHz to 100 kHz. Moreover, optimization method is proposed to realize the development of a wide-band, high-sensitivity, and low-noise induction magnetometer. First of all, the parameters related to the sensitivity of the sensor are investigated according to the law of electromagnetic induction. A three-dimensional finite element (3D-FE) simulation model was established to study the influence of various parameters of induction magnetometers. In addition, an analysis method combining orthogonal experiment and response surface method is adopted to reduce the quantity of computations and improve the efficiency of analysis. The orthogonal experiment is able to obtain preliminary optimal parameters with only a small amount of computation results. Based on the results of the orthogonal experiment, the response surface method is used to illustrate the relationship between the sensor parameters and losses, and hence the optimal sensor parameters can be obtained. Finally, the model is verified by other sets of simulations, and the results show the regression coefficient of the model $R^{2}=0.9735$ , indicating the effectiveness of the proposed model.
- Published
- 2022
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