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The equivalent circuit is an indispensable tool for analyzing the steady-state characteristics of the brushless doubly fed induction machine (BDFIM). However, the most commonly used equivalent circuits are not available to analyze some special operation modes, such as the natural synchronous mode with one set of winding powered by dc current. In order to overcome the limitation, in this article, a novel equivalent circuit is proposed. At first, the electromagnetic relations within BDFIMs are described by a new approach in which the cause of working magnetic fields is refined. Then, the equivalent circuit is built by the rigorous derivation of electromagnetic relations. And a few features of BDFIMs in some typical operation modes including the natural synchronous mode are introduced in details. Finally, the validity of the equivalent circuit is made by comparison of model and experimental results based on a wound-rotor BDFIM prototype. The proposed model with clear physical concept can cover all operation modes. And both power relationship and torque components reflected in the proposed model is more detailed and clearer than those reflected in the traditional one. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) strategy can provide significant benefits for controlling nonlinear systems over classical cascade field-oriented control (FOC). However, the MPC is still in the development stage for a high-performance predictive model. Therefore, the proposed MPC in this article updates the internal linear predictive model at each time step to accurately represent the nonlinear plant of a permanent-magnet synchronous motor (PMSM) plant over different speed regions. In other words, the adaptive discrete linear plant model (ADLPM) is designed to update the current operating conditions of the machine parameters and the equilibrium points of the measured stator currents, speed, and load torque. For the operation in the flux-weakening region, the proposed MPC depends on a performance control algorithm (PCA) to obtain high dynamic performance. In this PCA algorithm, the proposed MPC depends on the modified reference velocity rather than the original reference velocity, which can calculate the required d-axis current directly. Moreover, the proposed cost function is designed directly in terms of the error values of the velocity and d-axis current, which fits the motor performance based on the further constraint of the maximum magnitude of the drawn stator current provided to control the acceleration of the rotor. Finally, comprehensive simulations and experiments have fully demonstrated that the proposed MPC can reduce the speed drop, and torque ripple in response to those of the FOC and traditional MPC strategies. [ABSTRACT FROM AUTHOR]

The diversity of magnetic field information obtained in marine geomagnetic measurements is of great relevance to defining detailed features of the targets. In this article, a solution algorithm based on the combination of scalar and vector fields is proposed. The magnetic direction of the geomagnetic field was obtained by repeatedly applying bias fields, and the multiparameter integrated measurement is realized based on the geometric relationship of the geomagnetic parameters. To make an instrument feasible for undersea measurement, a miniaturized multiparameter magnetometer was constructed within the limited space of a pressure tank, using an Overhauser scalar sensor and a spherical coil for generating bias fields. Test platforms were built to evaluate the scalar sensor and spherical coil. Results from a nonmagnetic laboratory showed that the expanded uncertainty of the scalar sensor was 0.11 nT, whereas the magnetic field generated by the spherical coil had 97% uniformity and completely engulfed the scalar sensor. Moreover, field experiments indicated that the standard deviation of prototype instrument in magnetic direction (3 $^{\prime \prime }$) was close to that of declination–inclination magnetometer, whereas its standard deviation in Z-component of 0.24 nT was better than that of a commercial fluxgate magnetometer. It also had markedly better measurement stability, with no temperature drift. [ABSTRACT FROM AUTHOR]

The mission of detecting and locating unexploded ordnance (UXO) such as the landmine, the improvised explosive devised, etc., is still a challenge to be overcome. In this paper, a new active approach for UXO detection through measuring electromagnetic (EM) response with a magnetic sensor is proposed. To further enhance the magnetic field strength of the UXO, a current-carrying coil is employed to produce a time-varying or steady magnetic field, and a magnetic field modeling of the solenoid structure is built to select optimal coil parameters. To realize three-dimensional imaging, a magnetic field measurement array of $3\times3$ tri-axial magneto-inductive (MI) sensors is constructed, and its major electrical characteristics are evaluated. Finally, a test platform is developed, and the experimental results indicate that the proposed method can detect a plastic anti-personnel UXO down up to a depth of 20.1 cm, improving 50% approximately when compared with a commercial metal detector. [ABSTRACT FROM AUTHOR]

The winding theory is a crucial tool for analyzing the electric machines. However, some special phenomena in short primary linear machines (SPLMs) cannot be explained by the traditional theory, which is commonly applied in rotary machines (RMs). In this paper, an improved winding theory for SPLMs is presented. Starting with the magnetic field produced by a single conductor, the difference between winding theory for SPLMs and RMs is analyzed. According to the proposed theory, the pulsating magneto-motive force (MMF) and the asymmetry of the three-phase windings can be analyzed and calculated in details. It is very useful for perceiving, analysis and optimal design for the winding in SPLMs. The proposed theory is verified by 2-D finite-element analysis (FEA) and experiment. [ABSTRACT FROM AUTHOR]

In aeromagnetic surveys, poor aircraft heading and weather may frequently cause a classical optically-pumped sensor to enter into or close to its dead zone, which results in unavoidable outliers that seriously reduce aeromagnetic compensation. To address these problems, a method to identify rapidly and pre-cull magnetic outliers based on the gray system theory is proposed to reduce their negative influence during the estimation of coefficients and target detection robustness. By constructing a gray region of aeromagnetic data and then checking whether the data at the end points of the region are normal, aeromagnetic outliers can be culled. The simulation results show that even if the outlier rate is increased to 20%, the average of the correct culling rate of the proposed method can still reach 99.67%, at which the culling effect is highly robust. We constructed an experimental survey platform and conducted a flight test. The results show that the improvement ratio of the proposed method can reach 4.36, which is 10.38 times higher than the conventional method. [ABSTRACT FROM AUTHOR]

Magnetic target positioning methods that use magnetic gradient tensors have wide application prospects in unexploded ordnance detection, moving magnetic target tracking, and so on. However, the commonly used positioning methods, such as Nara, Frahm, and scalar triangulation and ranging (STAR), still have some problems. Namely, these methods cannot avoid the influence of the geomagnetic field, depend highly on sensor accuracy, and have poor tolerances to environmental noise, all of which severely restrict their practical applications. To overcome the aforementioned bottleneck, this article proposes a new two-point tensor positioning (TPTP) method based on a magnetic moment constraint. First, a two-point magnetic gradient tensor-measurement structure is built, and a target positioning function is constructed in which a penalty term with target magnetic moment information is introduced. Second, through simulation and comparative analysis, the approximate value range of the optimal penalty coefficient is delimited, and the objective function with penalty items greatly improves the optimization success rate. Finally, we compare the TPTP with state-of-the-art methods in various scenarios, including cases with and without geomagnetic fields, with different sensor accuracies, and with different levels of environmental noise. The experimental results indicate that the proposed TPTP method can effectively avoid the influence of the geomagnetic field. This method can also be used to realize the positioning and tracking of a magnetic target, even if the sensor accuracy is relatively low or the environmental noise is relatively large. [ABSTRACT FROM AUTHOR]

Earth magnetic field sensors are used to detect the geomagnetic field and are critical for research in the geosciences and in prospecting for mineral resources. Today, the Overhauser sensor is the most accurate scalar sensor among widely applied geomagnetic field sensors. However, the Overhauser sensor shows severe orientation sensitivity due to its solenoid induction coil. Hence, in mobile applications that use Overhauser sensors, the accuracy of geomagnetic field data is decreased because of this orientation sensitivity. This paper proposes a method of suppressing the orientation sensitivity of the Overhauser sensor from the perspectives of the sensor structure, signal conditioning circuit, and measurement algorithm. To address the problem of no signal output from the sensor in a certain orientation, the parameters of the solenoid coil are optimized. Moreover, we designed a frequency adaptive high-accuracy signal extraction method based on a closed-loop feedback strategy, to decrease the measurement error contributed by the signal conditioning circuit and frequency measurement algorithm. Finally, we implement a prototype device using the proposed method with the commercial instruments to characterize the performance of our prototype, and test the orientation sensitivity of the prototype in the standard magnetic metering station. Experimental results demonstrate that the proposed sensor can achieve high-accuracy measurement capabilities comparable to those of commercial instruments in any orientation, indicating that its orientation sensitivity is efficiently suppressed. [ABSTRACT FROM AUTHOR]

Achieving effective detection of unexploded ordnance (UXO) is of great significance for ensuring the safety of human lives and regional economic development. Differential magnetic tensor gradient systems have strong application prospects for UXO detection because of their low orientation requirements and exceptional sensitivity to weak magnetic fields. These systems usually have a hollow ring-shaped measurable range, referred to as the “measurable area”. With the rapid advancement of the tensor measurement system, it is necessary to further analyse the measurable area performance. In this paper, a simulation method based on a target magnetic dipole revolving around such a measurement system is designed for evaluating the measurable area. An improved Frobenius norm is adopted to compare the measured tensor data, and the centre distance is used instead of the baseline distance to better describe the scale of the measurement system. The measurable areas of planar cross-shaped, square, and triangular structures are studied, as well as the corresponding influencing factors. Finally, the quantitative relationships between the measurable area performance of the three structures and the magnetic dipole moment direction, the sensor accuracy, and the centre distance of the measurement system are obtained. [ABSTRACT FROM AUTHOR]

The initial orientation error of a coil vector magnetometer directly determines the measurement accuracy of the magnetic field direction. The traditional initial orientation method requires auxiliary manually operated instruments. To solve this problem, we propose an electrical orientation method based on applying bias fields. To analyze quantitatively the orientation error of the proposed method, a physical model for the coil orientation indicator and measurement errors of the magnetic direction was developed that exploits measurements of the deflected field obtained after applying two oppositely directed bias fields. The simulation results show that, when the difference indicator is 0.7 nT, the measurement error of the magnetic direction is less than $9\,''$. Moreover, when the bias field strength is greater than 30% of the geomagnetic field strength during the orientation operation, the influence of the change in strength of the bias field on the measurement error of the magnetic direction diminishes significantly. The indirect effect of the measurement error of the total-field sensor on the measurement accuracy of the magnetic direction was also analyzed. To verify this method, we designed an experimental setup and conducted a comparative experiment. The results show that as the difference indicator increases, the measurement error of the magnetic direction increases accordingly. When this indicator is adjusted to about 0.7 nT, the measurement error of the magnetic direction is less than $11.16''$ , which is in agreement with theoretical results. [ABSTRACT FROM AUTHOR]

Using a prior data to solve for the characteristic parameters of a moving magnetic target is crucial in its detection. For this purpose, we developed a real-time detection method using distributed scalar sensor networks based on a hybrid algorithm combining particle swarm optimization and the Gauss-Newton method. The magnetic anomaly fitting model of the target is established using the magnetic-dipole-moment principle. The PSO’s insensitivity to the initial solution is used to obtain a rough solution of the coefficients of the fitting, and then a more accurate solution is developed using the Gauss-Newton method, exploiting its advantage in high precision. Furthermore, to evaluate the proposed method, we built a test platform. The detection results show that the goodness-of-fit reaches 0.9565 and only requires 3.4 s; in the 16 m horizontal distance, the calculated trajectory overlaps significantly the actual trajectory, and errors in position and speed are around 10% and 4.25%, respectively. [ABSTRACT FROM AUTHOR]

A miniature magnetic gradient tensor system may be used in small spacecraft for mineral prospecting and detection of unexploded explosive ordnance. The system consists of a magneto-inductive (MI) sensors array, a signal extraction circuit, and a microcontroller. A magnetic gradient full-tensor configuration utilizes four MI sensors arranged in a planar cross structure and is employed to minimize orientation and orthogonality errors. The system's performance was checked by data validation and magnetic anomaly detection. Numerous experimental results demonstrate that the system is able to detect a low-amplitude magnetic field as low as 8.28 nT at 10 Hz, with a typical noise floor of 0.235 nT/Hz1/2 at 1 Hz. The system can identify nearby ferromagnetic objects clearly, which indicates its feasibility for weak magnetic anomaly detection. [ABSTRACT FROM AUTHOR]

The proton precession magnetometer (PPM) is always employed for geomagnetic observation, magnetic anomaly detection, etc., while the tuning performance of the PPM determines the signal-to-noise ratio (SNR) of the free induction decay (FID) signal output from the sensing coil. A tuned circuit was always used for the PPM sensing coil because of its narrow-band characteristic and high sensitivity. However, the FID signals might be distorted by the narrow bandwidth, which influences the PPM’s measurement accuracy for the geomagnetic field. To address this problem, we propose a tuning-matching framework consisting of an adjustable tuning capacitor network (ATCN) in parallel with a $\pi $ -type LC band-pass filter (LCBF), dubbed ATCN-LCBF. The equivalent circuit of the ATCN-LCBF are investigated and the corresponding electrical parameters are theoretically calculated. Consequently, the proposed ATCN-LCBF is conducted with a bandwidth of 3500 Hz, a pass-band gain of 5 dB, and an average noise floor of 1.67 nV/Hz1/2. The field experimental results demonstrate that the ATCN-LCBF can not only enhance the strength of the FID signal but also suppress the external noises, improving the signal detection performance of the PPM in a scenario with strong interference. [ABSTRACT FROM AUTHOR]

The sensor tuning of a proton precession magnetometer determines the signal-to-noise ratio (SNR) of induced free induction decay (FID) signal, while the quality of the FID influences the measurement accuracy of the geomagnetic field. Even though numerous methods have been proven to be effective in improving the tuning precision, how to efficiently decrease tuning error in a noisy environment is still a crucial challenge. To end this, a new tuning algorithm based on the combination of principal component analysis (PCA) and singular value decomposition (SVD), namely C-PCASVD, was presented in this paper. This novel algorithm aims to suppress the interference of the FID signal. The proposed C-PCASVD can obtain the dominant principal components of FID and noise, respectively. In addition, it is able to identify the corresponding singular values of interference, which could achieve an optimum trade-off between the denoised FID and noise reduction efficiency. The performance of the proposed method is tested on synthetic and field signals from different surveys. Good tuning frequency estimations are obtained at different SNRs. Through comparing the proposed C-PCASVD tuning algorithm with the state-of-the-art methods, including peak detection (PD), auto-correction and FFT (AC-FFT), and secondary tuning based on SVD (ST-SVD), the experimental results demonstrate that the C-PCASVD can significantly improve the tuning precision of proton precession magnetometer in a noisy environment. [ABSTRACT FROM AUTHOR]

Proton precession magnetometer (PPM) is a potential device to measure the low-frequency geomagnetic field in the time domain. Nevertheless, the uncontrollable noise such as power frequency noise, random noise, etc., severely affects the detection results. In this paper, aimed to boost the performance of the PPM, a novel real-time processing algorithm for the optimization of PPM output strategy based on the low-rank constraint (LRC) is proposed, and a new efficient framework, dubbed LRC-based geomagnetic data readout optimizer (LRC-GDRO), is implemented. This method aims to extract the dominant principal components of the pure magnetic signal and identify the singular values of noise. Thereby, the relative ideal signal without external noise, which still contains the ambient field information is yielded. Moreover, we develop a prototype device and compare the test results before and after using the proposed method. Consequently, compared with traditional PPM, the performance of the PPM using the proposed method has been significantly improved with a measurement accuracy of ± 0.2 nT. Furthermore, the experimental results reveal that the LRC-optimized PPM is comparable to a very high-accuracy Overhauser magnetometer in terms of 12 h geomagnetic field observation. [ABSTRACT FROM AUTHOR]

The outliers of the magnetic sensor that are inevitable in special aeromagnetic surveys reduce the robustness of ordinary least-squares (OLS), which are widely used for aeromagnetic compensation. To address this problem, we propose an aeromagnetic compensation algorithm based on the Huber loss method that is robust to outliers. In the proposed method, different weights are assigned to the inliers and outliers using an iteratively reweighted least-squares technique. Although the OLS performs similarly to the proposed method when only 1% of the data are outliers, it is theoretically verified that the proposed method can increase the goodness-of-fit to 0.9963, from 0.6618 in the case of OLS, in the presence of 10% outliers. An experimental platform was constructed to record real magnetic data, with special measures taken to ensure the presence of outliers in the collected data. The results of a flight test using this experimental platform demonstrate that the proposed method increases the improvement ratio to 4.14 from 2.46 when using the OLS. [ABSTRACT FROM AUTHOR]

Resonant cavity is an important component of Overhauser magnetometer sensor. Its function is to make the working substance generate dynamic nuclear polarization effect in the sensor. An alternative design of resonant cavity based on the birdcage coil structure is proposed to make the resonant frequency in accordance with the polarization frequency of the working substance. The structure and equivalent circuit of resonant cavity are analyzed. The model of resonant cavity is established, and S-parameter is calculated. The simulating results show that resonant frequency of the resonant cavity is about 60 MHz, which is consistent with the polarization frequency of the working substance in the sensor, and Q-factor of the resonant cavity is about 90. A dual-coil structure for pick-up coil and series resonant circuit are designed for reducing interference. In addition, output signal experiment and simultaneous comparison testing of sensor prototype are conducted. Overall, this design has the advantages of high performance and strong anti-interference. The resolution, uncertainty, and range of the sensor reach to 0.005 nT, 0.2 nT, and 20 000–100 000 nT, respectively. [ABSTRACT FROM PUBLISHER]

The measurement accuracy of the Larmor frequency of the Overhauser magnetic sensor directly determines the magnetic accuracy of the Overhauser magnetometer. We propose a multichannel interpolation method for marine magnetic measurements, addressing specifically the deficiencies in traditional measurement methods. The quantization error of the count value of the standard signal is greatly reduced using the delay chain interpolation technique. Also the influence arising from the phase error is weakened through channel expansion. In addition, we also design a test platform and conduct two sets of field contrast tests, the test results showing that the proposed method not only improves the precision of the frequency measurement by about three times but also improves the resolution and lowers the noise level of the system. [ABSTRACT FROM PUBLISHER]

An automatic wideband 90° phase shifter for optically pumped cesium magnetometer has been investigated experimentally. As an important part of the self-oscillating optically pumped cesium magnetometer detecting circuit, the band and automation of the phase shifter directly affect the continuous measurement of the magnetic field. At the same time, a phase deviation of 1° will cause 1 Hz change of the resonant frequency. In order to meet the continuous measurement of the geomagnetic field, an automatic wideband 90° phase shifter based on the all-pass filter has been designed. It can be used to precisely make the phase of the detected signal shifted by 90° in a wide range of frequencies from 50 to 350 kHz. Through the actual test and analysis, the phase shift error of the automatic phase shifter is less than 0.1°, and the relative error less than 0.1%. It has been proved the feasibility of the automatic wideband 90° phase shifter applied to the cesium optically pumped magnetometer. [ABSTRACT FROM PUBLISHER]