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: 20 May 2024 | Viewed by 1309

Special Issue Editors

College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130021, China
Interests: electromagnetic instrumentation; artificial intelligence algorithm; high-power transmitter; quadrature-phase-locked amplifier
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

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

14 pages, 2696 KiB  
Article
Analysis of Characteristics of the Electric Field Induced by an Angularly Rotating and Oscillating Magnetic Object
Appl. Sci. 2024, 14(3), 1321; https://doi.org/10.3390/app14031321 - 05 Feb 2024
Viewed by 331
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 xz 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)
Show Figures

Figure 1

16 pages, 6171 KiB  
Article
Artificial Neural Network Based Prediction of Long-Term Electric Field Strength Level Emitted by 2G/3G/4G Base Station
Appl. Sci. 2023, 13(19), 10621; https://doi.org/10.3390/app131910621 - 23 Sep 2023
Viewed by 708
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)
Show Figures

Figure 1

Back to TopTop