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Electromagnetic Detection Instruments and Signal Processing
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Electromagnetic Detection Instruments and Signal Processing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 3815

Special Issue Editors

Dr. Gang Li

E-Mail Website
Guest Editor
College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130021, China
Interests: electromagnetic instrumentation; artificial intelligence algorithm; high-power transmitter; quadrature-phase-locked amplifier
Dr. Chuandong Jiang

E-Mail Website
Guest Editor
College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130021, China
Interests: surface NMR for groundwater exploration; nuclear magnetic resonance; magnetic resonance
Dr. Haigen Zhou

E-Mail Website
Guest Editor
College of Instrumentation and Electrical Engineering, Jilin University, Changchun, 130021 China
Interests: electromagnetic ground exploration methods and instruments; electromagnetic emission and antenna technology; electromagnetic measurement and imaging; power electronics technology and equipment

Special Issue Information

Dear Colleagues,

Electromagnetic instrument systems are the foundation of deep mineral resources exploration, and the development of high-precision electromagnetic instruments is of great significance. Especially with the rapid progress of modern physics, electronic science, and computer technology, electromagnetic prospecting instruments are developing towards automation and intelligence. At the same time, the electromagnetic detection signal processing method integrates the latest artificial intelligence, deep learning, and machine learning methods, which greatly improves the detection accuracy. In this Special Issue, we seek high-quality submissions of original research articles regarding all aspects related to electromagnetic sounding instruments and signal processing. We welcome both theoretical and application papers of high technical standards across various disciplines, thus facilitating an awareness of techniques and methods in one area that may apply to others.

Topics of interest include but are not limited to:

  • EM instrument design;
  • Transmitting waveform and control;
  • Reciever technology;
  • Electromagnetic sensor;
  • Signal-processing algorithms;
  • Ground-penetrating radar.

Dr. Gang Li
Dr. Chuandong Jiang
Dr. Haigen Zhou
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • EM instrument
  • resonance transmitting
  • noise suppression
  • signal processing
  • intelligence algorithm
  • data analysis
  • calibration

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Published Papers (4 papers)

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Research

15 pages, 1614 KiB  
Article
Domain Decomposition and Model Order Reduction for Electromagnetic Field Simulations in Carbon Fiber Composite Materials
by Suyang Lou, Antoine Pierquin, Guillaume Wasselynck, Didier Trichet and Nicolas Bracikowski
Appl. Sci. 2024, 14(14), 6013; https://doi.org/10.3390/app14146013 - 10 Jul 2024
Viewed by 498
Abstract
The computation of the electric field in composite materials at the microscopic scale results in an immense number of degrees of freedom. Consequently, this often leads to prohibitively long computation times and extensive memory requirements, making direct computation impractical. In this study, one [...] Read more.
The computation of the electric field in composite materials at the microscopic scale results in an immense number of degrees of freedom. Consequently, this often leads to prohibitively long computation times and extensive memory requirements, making direct computation impractical. In this study, one employs an innovative approach that integrates domain decomposition and model order reduction to retain local information while significantly reducing computation time. Domain decomposition allows for the division of the computational domain into smaller, more manageable subdomains, enabling parallel processing and reducing the overall complexity of the problem. Model order reduction further enhances this by approximating the solution in a lower-dimensional subspace, thereby minimising the number of unknown variables that need to be computed. Comparative analysis between the results obtained from the reduced model and those from direct resolution demonstrates that our method not only reduces computation time but also maintains accuracy. The new method effectively captures the essential characteristics of the electric field distribution in composite materials, ensuring that the local phenomena are accurately represented. This study provides a contribution to the field of computational electromagnetics by presenting a feasible solution to the challenges posed by the high computational demands of simulating composite materials at the microscopic scale. The proposed methodology offers a promising direction for future research and practical applications, enabling more efficient and accurate simulations of complex material systems. Full article
(This article belongs to the Special Issue Electromagnetic Detection Instruments and Signal Processing)
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15 pages, 7520 KiB  
Article
Design and Analysis of Micro Signal Detection Circuit for Magnetic Field Detection Utilizing Coil Sensors
by Qifan Xu, Sichang Zhang, Siyu Li, Zhe Xu, Shouqi Cao and Meiling Wang
Appl. Sci. 2024, 14(9), 3618; https://doi.org/10.3390/app14093618 - 25 Apr 2024
Viewed by 920
Abstract
Eddy current inspection has been extensively employed in non-destructive testing of various conductive materials. The coil probe, as a mainstream sensor in the eddy current detection system, inevitably encounters interference from external signals while transmitting its own signal. Therefore, developing techniques to extract [...] Read more.
Eddy current inspection has been extensively employed in non-destructive testing of various conductive materials. The coil probe, as a mainstream sensor in the eddy current detection system, inevitably encounters interference from external signals while transmitting its own signal. Therefore, developing techniques to extract valuable signals from noisy ones is crucial for ensuring accurate detection. Carbon fiber composites not only possess significantly lower electrical conductivity compared to conventional metallic materials but also exhibit notable anisotropy. To address this issue, we designed an ‘8’ coil probe set where the excitation coil does not electromagnetically interfere with the detection coil. However, practical applications that require portability and miniaturization pose challenges when utilizing this coil probe set to identify carbon content or defects due to the typically weak output signal. To address this issue, this paper proposes a design that combines the ‘8’ structure of the planar coil probe with the principle of phase-locked amplification to create a dual-phase sensitive phase-locked amplification detection circuit. These specific design ideas were tested using a weak signal, which passed through the preamplifier, secondary amplifier, and band-pass filter comprising the target channel for signal amplification and noise filtering. The effective signal amplitude is proportional to the inverse phase difference between the direct current (DC) signal and inversely proportional to the amplitude of the signal. Finally, the DC signal was passed through an analog-to-digital converter (ADC). The analog-to-digital converter (A/D) is used to collect and calculate the DC signal, enabling the detection of weak electrical signals. Simulation experiments demonstrated that the signal detection circuit has an amplitude error below 0.2% and a phase error below 0.5%. The phase-locked amplification circuit designed in this paper can effectively extract the tiny impedance change signals of the planar coil sensor probe with high sensitivity and good robustness. Full article
(This article belongs to the Special Issue Electromagnetic Detection Instruments and Signal Processing)
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14 pages, 2696 KiB  
Article
Analysis of Characteristics of the Electric Field Induced by an Angularly Rotating and Oscillating Magnetic Object
by Jiawei Zhang, Dawei Xiao, Taotao Xie and Qing Ji
Appl. Sci. 2024, 14(3), 1321; https://doi.org/10.3390/app14031321 - 5 Feb 2024
Viewed by 809
Abstract
A mathematical model for an electric field induced by an angularly oscillating magnetic dipole was proposed with magnetic vector potential to analyze the characteristics of the electric field induced by a rotating and angularly oscillating magnetic object. This mathematical model was constructed for [...] Read more.
A mathematical model for an electric field induced by an angularly oscillating magnetic dipole was proposed with magnetic vector potential to analyze the characteristics of the electric field induced by a rotating and angularly oscillating magnetic object. This mathematical model was constructed for the electric field induced by a magnetic object oscillating at a certain angle. On this basis, the phase relationship among the three components of the induced electric field was analyzed (defining the right-hand Cartesian coordinate system). Evidently, a phase difference of π/2 always existed between the horizontal components of the electric field induced by a magnetic dipole rotating around the z-axis. The phase difference between the vertical and transverse components in the x–z plane was also π/2. A phase difference of π was observed in the y–z plane. The above theoretical analysis was verified through simulation and experiment. The results showed that the frequency of the induced electric field was related to the angular velocity and angle of rotation. The amplitude was associated with the magnetic moment and the angular velocity and angle of oscillation. The maximum amplitude did not exceed the amplitude of the electric field induced by a magnetic object angularly oscillating at the same velocity. With regard to the amplitude and phase relationship, the three components of the induced electric field measured in the experiment were consistent with the results of the theoretical analysis. Full article
(This article belongs to the Special Issue Electromagnetic Detection Instruments and Signal Processing)
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16 pages, 6171 KiB  
Article
Artificial Neural Network Based Prediction of Long-Term Electric Field Strength Level Emitted by 2G/3G/4G Base Station
by Begum Korunur Engiz
Appl. Sci. 2023, 13(19), 10621; https://doi.org/10.3390/app131910621 - 23 Sep 2023
Viewed by 1106
Abstract
Accurate predictions of radio frequency electromagnetic field (RF-EMF) levels can help implement measures to reduce exposure and check regulatory compliance. Therefore, this study aims to predict the RF-EMF levels in the medium using an artificial neural network (ANN). The work was conducted at [...] Read more.
Accurate predictions of radio frequency electromagnetic field (RF-EMF) levels can help implement measures to reduce exposure and check regulatory compliance. Therefore, this study aims to predict the RF-EMF levels in the medium using an artificial neural network (ANN). The work was conducted at Ondokuz Mayis University, Kurupelit Campus, where the measurement location has line-of-sight to the base stations. Band selective measurements were also performed to assess the contribution of 2G/3G/4G services to the total RF-EMF level, which was found to be the highest among all services within the total band. Long-term RF-EMF measurements were carried out for 35 days within the frequencies of 100 kHz to 3 GHz. Then, an ANN model with Levenberg–Marquardt (LM) and Bayesian Regulation (BR) algorithms was proposed, which utilized inputs from real-time RF-EMF measurements. The performance of the models was assessed in terms of mean squared error (MSE) and regression performance. The average MSE and regression performances of the models were similar, with the lowest testing MSEs of 2.78 × 10−3 and 3.76 × 10−3 for LM and BR methods, respectively. The analysis of the models showed that the proposed models help to predict the RF-EMF level in the medium with up to 99% accuracy. Full article
(This article belongs to the Special Issue Electromagnetic Detection Instruments and Signal Processing)
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