Study of the Low-Frequency Excess Equivalent Magnetic Noise in GMI-Based Devices

Portalier, Elodie; Dufaÿ, Bruno; Dolabdjian, Christophe; Seddaoui, D.; Yelon, A.; Ménard, David

doi:10.1109/jsen.2017.2748601

Cited by 3 publications

(3 citation statements)

References 17 publications

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“…In the middle and high frequencies (more than 1 kHz), Barkhausen noise is the mainstay, and it is caused by the complex magnetic domain structure forming the ferromagnetic material and the displacement and rotation of the domain wall during magnetization [10,11]. In the low frequencies (less than 1 kHz), the thermomagnetic noise caused by the thermal fluctuation of magnetization contributes significantly to the intrinsic noise of the GMI to the intrinsic noise of the GMI component through impedance fluctuations [12,13]. The intrinsic noise of the GMI component is 2~3 magnitudes [14] lower than that of the conditioning circuit.…”

Section: Introductionmentioning

confidence: 99%

“…These modules should be given priority in the optimization of the noise of the conditioning circuit. The above results provide technical support for the practical application of low-noise GMI magnetometers.Sensors 2020, 20, 960 2 of 13 component through impedance fluctuations [12,13]. The intrinsic noise of the GMI component is 2~3 magnitudes [14] lower than that of the conditioning circuit.…”

mentioning

confidence: 99%

“…Sensors 2020, 20, 960 2 of 13 component through impedance fluctuations [12,13]. The intrinsic noise of the GMI component is 2~3 magnitudes [14] lower than that of the conditioning circuit.…”

mentioning

confidence: 99%

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Noise Modeling and Simulation of Giant Magnetic Impedance (GMI) Magnetic Sensor

Jin

Wang

et al. 2020

Sensors

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The detection resolution of a giant magneto-impedance (GMI) sensor is mainly limited by its equivalent input magnetic noise. The noise characteristics of a GMI sensor are evaluated by noise modeling and simulation, which can further optimize the circuit design. This paper first analyzes the noise source of the GMI sensor. It discusses the noise model of the circuit, the output sensitivity model and the modeling process of equivalent input magnetic noise. The noise characteristics of three modules that have the greatest impact on the output noise are then simulated. Finally, the simulation results are verified by experiments. By comparing the simulated noise spectrum curve and the experimental noise spectrum curve, it is demonstrated that the preamplifier and the multiplier contribute the most to the output white noise, and the low-pass filter plays a major role in the output 1/f noise. These modules should be given priority in the optimization of the noise of the conditioning circuit. The above results provide technical support for the practical application of low-noise GMI magnetometers.Sensors 2020, 20, 960 2 of 13 component through impedance fluctuations [12,13]. The intrinsic noise of the GMI component is 2~3 magnitudes [14] lower than that of the conditioning circuit. Above all, the conditioning circuit is the main factor of noise sources [15][16][17], and it is mainly studied in this paper.Conditioning circuit noise is inherent noise inside an electronic system, which is caused by the random motion of the charge carriers. It includes the thermal noise of the resistor [18,19], the shot noise of the PN junction and the 1/f noise [20,21]. For the GMI sensor, the conditioning circuit structure is divided into two parts: the excitation circuit and the detection circuit. The excitation circuit mainly includes an incentive source and voltage-to-current converter [22]. The detection circuit includes a preamplifier, a peak detection circuit and an instrumentation amplifier [23,24]. Each part contains multiple noise sources, and the noise effect contributes differently to the total output noise of the sensor. According to the Fries theorem, in order to achieve the best noise characteristics, the signal-to-noise ratio and the equivalent input noise voltage are generally used to weigh and design the various parts of the system [25,26]. Therefore, by modeling the noise of each module in MATLAB, the dominant noise source is found, allowing further optimization of the dominant noise source and significantly improving the noise characteristics of the conditioning circuit.The work of this paper is divided into three steps: firstly, the modeling idea of the equivalent input magnetic noise model of a GMI sensor is discussed. The output voltage noise model, sensitivity model and equivalent input magnetic noise model are established. Then the noise contribution of each module is computed, and the optimization scheme of the dominant noise source is discussed. Finally, the effectiveness of the noise optimization method is verifie...

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Noise Modeling and Simulation of Giant Magnetic Impedance (GMI) Magnetic Sensor

Jin

Wang

et al. 2020

Sensors

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Theoretical and Experimental Investigation of Temperature-Compensated off-diagonal GMI Magnetometer and its long-term Stability

Esper¹,

Dufaÿ²,

Saez³

et al. 2020

IEEE Sensors J.

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Off-Diagonal Magnetoimpedance in Annealed Amorphous Microwires with Positive Magnetostriction: Effect of External Stresses

Buznikov

2023

Magnetism

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It was observed recently that the giant magnetoimpedance (GMI) effect in Fe-rich glass-coated amorphous microwires with positive magnetostriction can be improved significantly by means of post-annealing. The increase in the GMI is attributed to the induced helical magnetic anisotropy in the surface layer of the microwire, which appears after the annealing. The application of external stresses to the microwire may result in changes in its magnetic structure and affect the GMI response. In this work, we study theoretically the influence of the tensile and torsional stresses on the off-diagonal magnetoimpedance in annealed amorphous microwires with positive magnetostriction. The static magnetization distribution is analyzed in terms of the core–shell magnetic structure. The surface impedance tensor is obtained taking into account the magnetoelastic anisotropy induced by the external stresses. It is shown that the off-diagonal magnetoimpedance response exhibits strong sensitivity to the magnitude of the applied stress. The obtained results may be useful for sensor applications of amorphous microwires.

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Study of the Low-Frequency Excess Equivalent Magnetic Noise in GMI-Based Devices

Cited by 3 publications

References 17 publications

Noise Modeling and Simulation of Giant Magnetic Impedance (GMI) Magnetic Sensor

Noise Modeling and Simulation of Giant Magnetic Impedance (GMI) Magnetic Sensor

Theoretical and Experimental Investigation of Temperature-Compensated off-diagonal GMI Magnetometer and its long-term Stability

Off-Diagonal Magnetoimpedance in Annealed Amorphous Microwires with Positive Magnetostriction: Effect of External Stresses

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