Search Results (61)

An electrocardiogram (ECG) is a vital diagnostic tool that provides crucial insights into the heart rate, cardiac positioning, origin of electrical potentials, propagation of depolarization waves, and the identification of rhythm and conduction irregularities. Analysis of ECG is essential, especially during pregnancy, where monitoring fetal health is critical. Fetal electrocardiography (fECG) has emerged as a significant modality for evaluating the developmental status and well-being of the fetal heart throughout gestation, facilitating early detection of congenital heart diseases (CHDs) and other cardiac abnormalities. Typically, fECG signals are acquired non-invasively through electrodes placed on the maternal abdomen, which reduces risk and enhances user convenience. However, these signals are often contaminated via various sources, including maternal electrocardiogram (mECG), electromagnetic interference from power lines, baseline drift, motion artifacts, uterine contractions, and high-frequency noise. Such disturbances impair signal fidelity and threaten diagnostic accuracy. This scoping review adhering to PRISMA-ScR guidelines aims to highlight the methods for signal acquisition, existing databases for validation, and a range of algorithms proposed by researchers for improving the quality of fECG. A comprehensive examination of 157,000 uniquely identified publications from Google Scholar, PubMed, and Web of Science have resulted in the selection of 6210 records through a systematic screening of titles, abstracts, and keywords. Subsequently, 141 full-text articles were considered eligible for inclusion in this study (from 1950 to 2026). By critically evaluating established techniques in the current literature, a strategy is proposed for analyzing fECG and calculating heart rate variability (HRV) for identifying fetal heart-related abnormalities. Advances in these methodologies could significantly aid in the diagnosis of fetal heart diseases, assisting timely clinical interventions and prevention. Full article

The study was based on 11 years of measurements of ionospheric parameters and atmospheric electric fields reflecting the polarity of lightning discharges and recording return strokes. The response of ionospheric parameters to thunderstorms with lightning discharges of negative and positive polarity under quiet solar and geomagnetic conditions was considered. No changes in the dynamics of ionospheric parameters are observed during thunderstorms with lightning discharges of negative polarity. Variation in the daily course of total electron content and the appearance of wave-like disturbances with a period of 2–5 h are recorded during thunderstorms with lightning discharges of positive polarity. More small-scale disturbances were also detected. Intensification of the sporadic layer was observed in ~70% of the thunderstorm events with positive lightning discharges. A decrease in the height of the sporadic layer Es (h’Es) by 10 km and an increase in the level of radio wave absorption in the D region of the ionosphere were recorded. The experimental results of the study indicate that the polarity of lightning discharges and electromagnetic effects play a decisive role in the process of thunderstorms affecting the ionosphere. Full article

The rapid growth of inverter-based resources (IBRs) has created a need for new islanding detection methodologies to determine whether an IBR has been disconnected from the transmission grid in some manner (islanded) or remains connected to the transmission grid (grid-connected). Active islanding detection methods inject a signal into the power system to achieve detection. Existing schemes frequently limit consideration to a single node system with one IBR. Schemes tested on multiple IBRs often see interference, with the signals from one IBR disturbing the others, or require intricate communication. Further, several methods destabilize an islanded grid to detect it, preventing a prospective microgrid from remaining in operation while islanded. This work develops an active islanding detection scheme using Pulse Compression Probing (PCP) that is microgrid-compatible and can be used with multiple IBRs without requirement for communication. This active islanding detection scheme can be implemented on existing inverter switching sequences and has a detection time of 167–223 ms, well within the detection time specified by existing standards. The method is verified via electromagnetic transient (EMT) simulation on a modified version of a 34-bus test system. Full article

Hydrodynamic slamming loads during water landing are one of the main concerns for the structural design and wave resistance performance of large amphibious aircraft. However, current existing sensors are not used for full-scale hydrodynamic load flight tests on complex models due to their large size, fragility, intrusiveness, limited range, frequency response limitations, accuracy issues, and low sampling frequency. Fibre-optic sensors’ small size, immunity to electromagnetic interference, and reduced susceptibility to environmental disturbances have led to their progressive development in maritime and aeronautic fields. This research proposes a novel hydrodynamic profile encapsulation method using ultra-thin surface-mounted micro-electromechanical system (MEMS) fibre-optic Fabry–Pérot pressure sensors (total thickness of 1 mm). The proposed sensor exhibits an exceptional linear response and low-temperature sensitivity in hydrostatic calibration tests and shows superior response and detection accuracy in water-entry tests of wedge-shaped bodies. This work exhibits significant potential for the in situ monitoring of hydrodynamic loads during water landing, contributing to the research of large amphibious aircraft. Furthermore, this research demonstrates, for the first time, the proposed surface-mounted pressure sensor in conjunction with a high-speed acquisition system for the in situ monitoring of hydrodynamic pressure on the hull of a large amphibious prototype. Following flight tests, the sensors remained intact throughout multiple high-speed hydrodynamic taxiing events and 12 full water landings, successfully acquiring the complete dataset. The flight test results show that this proposed pressure sensor exhibits superior robustness in extreme environments compared to traditional invasive electrical sensors and can be used for full-scale hydrodynamic load flight tests. Full article

Pulsed eddy current (PEC) testing technology has been widely used in the field of non-destructive testing of metal grounding structures due to its wide-band excitation and response characteristics. However, multi-source noise in industrial environments can significantly degrade the performance of PEC sensors, thereby limiting their detection accuracy. This study proposes a multi-modal joint pulsed eddy current signal sensor denoising method that integrates the inductive disturbance mechanism. This method constructs the Improved Whale Optimization -Variational Mode Decomposition-Singular Value Decomposition-Wavelet Threshold Denoising (IWOA-VMD-SVD-WTD) fourth-order processing architecture: IWOA adaptively optimizes the VMD essential variables (K, α) and employs the optimized VMD to decompose the perception coefficient (IMF) of the PEC signal. It utilizes the correlation coefficient criterion to filter and identify the primary noise components within the signal, and the SVD-WTD joint denoising model is established to reconstruct each component to remove the noise signal received by the PEC sensor. To ascertain the efficacy of this approach, we compared the IWOA-VMD-SVD-WTD method with other denoising methods under three different noise levels through experiments. The test results show that compared with other VMD-based denoising techniques, the average signal-to-noise ratio (SNR) of the PEC signal received by the receiving coil for 200 noise signals in different noise environments is 24.31 dB, 29.72 dB and 29.64 dB, respectively. The average SNR of the other two denoising techniques in different noise environments is 15.48 dB, 18.87 dB, 18.46 dB and 19.32 dB, 27.13 dB, 26.78 dB, respectively, which is significantly better than other denoising methods. In addition, in practical applications, this method is better than other technologies in denoising PEC signals and successfully achieves noise reduction and signal feature extraction. This study provides a new technical solution for extracting pure and impurity-free PEC signals in complex electromagnetic environments. Full article

A complex study was performed of the disturbances in geophysics parameters that were observed during a short-term period of earthquake preparation. On 4 March 2024, an $M6.1$ earthquake (N 42.93, E 76.966) occurred with the epicenter 12.2 km apart from the complex of geophysical monitoring. Preparation of the earthquake we detected in real time, 8 days prior to the main shock, when a characteristic cove-like decrease appeared in the gamma-ray flux measured 100 m below the surface of the ground, which observation indicated an approaching earthquake with high probability. Besides the gamma-ray flux, anomalies connected with the earthquake preparation were studied in the variation of the Earth’s natural pulsed electromagnetic field (ENPEMF) at very low frequencies (VLF) $f=7.5$ kHz and $f=10.0$ kHz and at ultra-low frequency (ULF) in the range of 0.001–20 Hz, as well as in the shift of Doppler frequency (DFS) of the ionospheric signal. A drop detected in DFS agrees well with the decrease in gamma radiation background. A sequence of disturbance appearance was revealed, first in the variations of ENPEMF in the VLF band and of the subsurface gamma-ray flux, both of which reflect the activation dynamic of tectonic processes in the lithosphere, and next in the variation of DFS. Two types of earthquake-connected effects may be responsible for the transmission of the perturbation from the lithosphere into the ionosphere: the ionizing gamma-ray flux and the ULF/VLF emission, as direct radiation from the nearby earthquake source. In the article, we emphasize the role of medium ionization in the propagation of seismogenic effects as a channel for realizing the lithosphere–ionosphere coupling. Full article

One of the main challenges in the operation of electric traction vehicles is ensuring safety and operational reliability. To ensure the safety of railway traffic, vehicles must undergo a series of tests related to the investigation of disturbances generated, among others, in the return current to the mains. This problem is further complicated by the inability to perform such measurements under laboratory conditions. The implementation of tests under real conditions determines the appearance of additional potential interference sources, from power sources to improper interactions between current collectors and the overhead contact system, and it requires strict compliance with regulatory standards and the implementation of standardized testing procedures. This article presents issues related to the investigation and analysis of the electromagnetic compatibility of rolling stock with train detection systems using track circuits. The aim of these tests is to determine the harmonic components in the traction current in relation to the permissible levels specified in the latest editions of the European Railway Agency—ERA/ERTMS/033281 version 5.0 documents and Annex S-02 to the List of the President of the Office of Rail Transport. The measurement methodology and test procedures are presented in detail with respect to current legal requirements. Full article

Every day, millions of meteoroids enter the atmosphere and ablate, forming a long plasma trail. It is a strongly scattering object for electromagnetic waves and can be effectively detected by meteor radar at altitudes between 70 km and 140 km. Its echo typically has Fresnel oscillation characteristics. Most of the traditional detection methods rely on determining the threshold value of the signal-to-noise ratio (SNR) and solving parameters to recognize meteor echoes, making them highly susceptible to interference. In this paper, a neural network model, YOLOv8n-BP, was proposed for detecting the echoes of underdense meteors by identifying them from their echo characteristics. The model combines the strengths of both YOLOv8 and back propagation (BP) neural networks to detect underdense meteor echoes from Range-Time-Intensity (RTI) plots where multiple echoes are present. In YOLOv8, the n-type parameter represents the lightweight version of the model (YOLOv8n), which is the smallest and fastest variant in the YOLOv8 series, specifically designed for resource-constrained scenarios. Experiments show that YOLOv8n has excellent recognition ability for underdense meteor echoes in RTI plots and can automatically extract underdense meteor echoes without the influence of radio-frequency interference (RFI) and disturbance signals. Limited by the labeling error of the dataset, YOLOv8 is not precise enough in recognizing the head and tail of meteors in the radar echograms, which may result in the extraction of imperfect echoes. Utilizing the Fresnel oscillation properties of meteor echoes, a BP network based on a Gaussian activation function is designed in this paper to enable it to detect meteor head and tail positions more accurately. The YOLOv8n-BP model can quickly and accurately detect and extract underdense meteor echoes from RTI plots, providing correct data for meteor parameters such as radial velocities and diffusion coefficients, which are used to allow wind field calculations and estimate atmospheric temperature. Full article

Continuous-wave (CW) radar sensors can remotely measure respiration and heartbeat by detecting the periodic movements of internal organs. However, external disturbances, such as random body motion (RBM) or environmental interference, significantly degrade the signal-to-noise ratio (SNR) and reduce the accuracy of vital sign detection. The various motion cancellation techniques that have been proposed to enhance robustness against RBMs include improvements in radar architecture, advanced signal processing algorithms, and studies on electromagnetic propagation characteristics. This paper provides a comprehensive review of recent advancements in motion cancellation techniques for CW radar-based vital sign detectors and discusses future research directions to improve detection performance in dynamic environments. Full article

Faulty synchronizations of synchronous generators can cause significant detrimental effects, primarily due to a large current and high electromagnetic torque. These effects not only impact the generator but they can also extend to the prime mover and the step-up transformer. Furthermore, such events can trigger disturbances in the power system, potentially leading to system collapse if not promptly cleared. Although the autosynchronizers and synchro-check technologies are well established in the industry, faulty synchronizations, such as those caused by incorrect wiring during maintenance or commissioning operations, can go undetected by these systems. Existing protections do not allow for the detection of faulty synchronizations in a timely manner. This paper presents novel protection methods specifically designed for this issue: one based on instantaneous current value and the other on the instantaneous current-derivative value. These schemes are activated exclusively during the synchronizations process, allowing for faster fault detection compared to existing methods, thereby reducing the duration of harmful electrical and mechanical stresses after a faulty synchronization. The effectiveness of the proposed schemes has been validated through computer simulations of a 362 MVA turbo-generator from a thermal power plant and also through experimental tests on a 5 kVA synchronous generator using a specialized laboratory synchronization test bench, yielding promising results. Full article

The China Seismo-Electromagnetic Satellite (CSES-01) is the first satellite of the space-based observational platform for the earthquake (EQ) monitoring system in China. It aims to monitor the ionospheric disturbances related to EQ activities by acquiring global electromagnetic fields, ionospheric plasma, energy particles, etc., opening a new path for innovative explorations of EQ prediction. This study analyzed 47 shallow strong EQ cases (Ms ≥ 7 and depth ≤ 100 km) recorded by CSES-01 from its launch in February 2018 to February 2023. The results show that: (1) For the majority (90%) of shallow strong EQs, at least one payload onboard CSES-01 recorded discernible abnormal signals before the mainshocks, and for over 65% of EQs, two or three payloads simultaneously recorded ionospheric disturbances; (2) the majority of anomalies recorded by different payloads onboard CSES-01 predominantly manifest within one week before or on the mainshock day, or occasionally about 11–15 days or 20–25 days before the mainshock; (3) typically, the abnormal signal detected by CSES-01 does not directly appear overhead the epicenter, but rather hundreds of kilometers away from the epicenter, and more preferably toward the equatorward direction; (4) the anomaly recognition rate of each payload differs, with the highest rate reaching more than 70% for the Electric Field Detector (EFD), Search-Coil Magnetometer (SCM), and Langmuir Probe (LAP); (5) for the different parameters analyzed in this study, the plasma density from LAP, and electromagnetic field in the ULF band recorded by EFD and SCM, and energetic electrons from the High-Energy Particle Package (HEPP) show a relatively high occurrence of abnormal phenomena during the EQ time. Although CSES-01 has recorded prominent ionospheric anomalies for a significant portion of EQ cases, it is still challenging to accurately extract and confirm the real seismic precursor signals by relying solely on a single satellite. The combination of seismology, electromagnetism, geodesy, geochemistry, and other multidisciplinary means is needed in the future’s exploration to get infinitely closer to addressing the global challenge of EQ prediction. Full article

Electronic power converters are widespread and crucial components in modern energy scenarios. Beyond mere electrical energy conversion, their electronic structure allows several functionalities to be naturally embedded in them, including energy management, diagnosis, communication, etc. The operation of the converter itself, or the system interfaced by the same, commonly produces undesired electromagnetic interferences (EMIs) that should comply with prescribed limits. This paper presents a digital active EMI filter designed to mitigate such disturbances. The proposed hardware implementation can acquire and analyze the common-mode (CM) noise affecting the circuit and inject a compensation signal to attenuate the measured interference. A novel adaptive algorithm is introduced to compute the necessary signals for effective noise cancellation. The implementation is integrated within a single printed circuit board interfaced with a field-programmable gate array (FPGA) running the control algorithm. The digital filter’s efficacy in EMI reduction is demonstrated using a synchronous buck converter with gallium nitride (GaN) power devices, achieving significant noise reduction. Additionally, potential functionalities are envisioned to fully exploit the capabilities of the proposal beyond EMI filtering, like fault detection, predictive maintenance, smart converter optimization, and communication. Full article

The Lithospheric–Atmospheric–Ionospheric Coupling (LAIC) mechanism stands as the leading model for the prediction of seismic activities. It consists of a cascade of physical processes that are initiated days before a major earthquake. The onset is marked by the discharge of ionized gases, such as radon, through subterranean fissures that develop in the lead-up to the quake. This discharge augments the ionization at the lower atmospheric layers, instigating disturbances that extend from the Earth’s surface to the lower ionosphere. A critical component of the LAIC sequence involves the distinctive perturbations of Extremely Low Electromagnetic Frequencies (ELF) within the Schumann Resonances (SR) spectrum of 2 to 50 Hz, detectable days ahead of the seismic event. Our study examines 10 earthquakes that transpired over a span of 3.5 months—averaging nearly three quakes monthly—which concurrently generated 45 discernible potential precursor seismic signals. Notably, each earthquake originated in Southern Greece, within a radius of 30 to 250 km from the observatory on Mount Parnon. Our research seeks to resolve two important issues. The first concerns the association between specific ELF signals and individual earthquakes—a question of significant importance in seismogenic regions like Greece, where earthquakes occur frequently. The second inquiry concerns the parameters that determine the detectability of an earthquake by a given station, including the requisite proximity and magnitude. Initial findings suggest that SR signals can be reliably linked to a particular earthquake if the observatory is situated within the earthquake’s preparatory zone. Conversely, outside this zone, the correlation becomes indeterminate. Additionally, we observe a differentiation in SR signals based on whether the earthquake took place over land or offshore. The latter category exhibits unique signal behaviors, potentially attributable to the water layers above the epicenter acting as a barrier to the ascending gases, thereby affecting the atmospheric–ionospheric ionization process. Full article

Islanding occurs when a load is energized solely by local generators and can result in frequency and voltage instability, changes in current, and poor power quality. Poor power quality can interrupt industrial operations, damage sensitive electrical equipment, and induce outages upon the resynchronization of the island with the grid. This study proposes an islanding detection method employing a Duffing oscillator to analyze voltage fluctuations at the point of common coupling (PCC) under a high-noise environment. Unlike existing methods, which overlook the noise effect, this paper mitigates noise impact on islanding detection. Power system noise in PCC measurements arises from switching transients, harmonics, grounding issues, voltage sags and swells, electromagnetic interference, and power quality issues that affect islanding detection. Transient events like lightning-induced traveling waves to the PCC can also introduce noise levels exceeding the voltage amplitude by more than seven times, thus disturbing conventional detection techniques. The noise interferes with measurements and increases the nondetection zone (NDZ), causing failed or delayed islanding detection. The Duffing oscillator nonlinear dynamics enable detection capabilities at a high noise level. The proposed method is designed to detect the PCC voltage fluctuations based on the IEEE standard 1547 through the Duffing oscillator. For the voltages beyond the threshold, the Duffing oscillator phase trajectory changes from periodic to chaotic mode and sends an islanded operation command to the inverter. The proposed islanding detection method distinguishes switching transients and faults from an islanded operation. Experimental validation of the method is conducted using a 3.6 kW PV setup. Full article

This paper introduces a robust waveform design method aimed at reducing the impact of electromagnetic interference in radar systems, thereby enhancing target detection accuracy. We propose utilizing a high-order p-norm to characterize the peak sidelobe level (PSL) of the waveform. Additionally, the method incorporates spectral zero-trapping within known interfering frequency bands to mitigate interference effects. A unified optimization objective function is developed to ensure optimal correlation properties of waveforms for dual-use in radar and communication systems. By employing the AdamW algorithm for dynamic adjustment of the iteration factor, combined with a gradient descent search, this method refines both the autocorrelation of the waveform and its resilience to known disturbances. Experimental results demonstrate that our approach significantly improves autocorrelation performance over randomly generated initial waveforms. Moreover, the introduction of spectral zero-trapping notably enhances interference suppression in targeted frequency bands, thereby boosting overall signal performance. Our method effectively balances interference rejection with the minimization of sidelobe levels, offering a pragmatic waveform solution for complex radar environments. Full article