Search Results (333)

Multiple input multiple output (MIMO) antennas have recently received attention for improving wireless communication data rates in rich scattering environments. Despite this, the challenge of isolation persists prominently in compact MIMO-based electronics. Various techniques have recently emerged to address the isolation issues, among which the defected ground structure (DGS) stands out as a cost-effective solution. Additionally, selecting the appropriate feed mechanism is crucial for enhancing the key performance indicators of MIMO antennas. However, there has been minimal focus on how different feed methods impact the operation of MIMO antennas integrated with DGS. This paper begins with a comprehensive review of diverse antenna design, feeding strategies, and DGS architectures. Subsequently, the causal relationships between various feed networks and DGSs has been established through modeling, simulation, fabrication, and measurement of MIMO antennas operating within the sub-6 GHz spectrum. Particularly, dual elements of MIMO antennas grounded by a slotted complementary split ring resonator (SCSRR)-based DGS were excited using four standard feed methods: coaxial probe, microstrip line, proximity coupled, and aperture coupled feed. The influence of each feed network on the performance of MIMO antennas integrated with SCSRR-based DGSs has been thoroughly investigated and compared, leading to guidelines for feed network selection. The coaxial probe feed network provided improved isolation performance, ranging from 16.5 dB to 46 dB in experiments.The aperture and proximity-coupled feed network provided improvements in bandwidth of 38.7% and 15.6%, respectively. Furthermore, reasonable values for envelope correlation coefficient (ECC), diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG) have been ascertained. Full article

Bearings are pivotal components of rotating machines where any defects could propagate and trigger systematic failures. Once faults are detected, accurately predicting remaining useful life (RUL) is essential for optimizing predictive maintenance. Although data-driven methods demonstrate promising performance in direct RUL prediction, their robustness and practicability need further improvement regarding physical interpretation and uncertainty quantification. This work leverages variational neural networks to model bearing degradation behind envelope spectra. A convolutional variational autoencoder for regression (CVAER) is developed to probabilistically predict RUL distributions with confidence measures. Enhanced average envelope spectra (AES) are used as network input for its physical robustness in bearing condition assessment and fault detection. The use of the envelope spectrum ensures that it contains only bearing-related information by removing other rotor-related frequencies, hence it improves the RUL prediction. Unlike traditional variational autoencoders, the probabilistic regressor and latent generator are formulated to quantify uncertainty in RUL estimates and learn meaningful latent representations conditioned on specific RUL. Experimental validations are conducted on vibration data collected using multiple accelerometers whose natural frequencies cover bearing resonance ranges to ensure fault detection reliability. Beyond conventional bearing diagnosis, envelope spectra are extended for statistical RUL prediction integrating physical knowledge of actual defect conditions. Comparative and ablation studies are conducted against benchmark models to demonstrate their effectiveness. Full article

Two enigmatic gamma-ray features in the galactic central region, known as Fermi Bubbles (FBs), were found from Fermi-LAT data. An energy release, (e.g., by tidal disruption events in the Galactic Center, GC), generates a cavity with a shock that expands into the local ambient medium of the galactic halo. A decade or so ago, a phenomenological model of the FBs was suggested as a result of routine star disruptions by the supermassive black hole in the GC which might provide enough energy for large-scale structures, like the FBs. In 2020, analytical and numerical models of the FBs as a process of routine tidal disruption of stars near the GC were developed; these disruption events can provide enough cumulative energy to form and maintain large-scale structures like the FBs. The disruption events are expected to be ${10}^{-4}\sim {10}^{-5}{\mathrm{yr}}^{-1}$, providing an average power of energy release from the GC into the halo of $\dot{\mathcal{E}}\sim 3\times {10}^{41}$ erg ${\mathrm{s}}^{-1}$, which is needed to support the FBs. Analysis of the evolution of superbubbles in exponentially stratified disks concluded that the FB envelope would be destroyed by the Rayleigh–Taylor (RT) instabilities at late stages. The shell is composed of swept-up gas of the bubble, whose thickness is much thinner in comparison to the size of the envelope. We assume that hydrodynamic turbulence is excited in the FB envelope by the RT instability. In this case, the universal energy spectrum of turbulence may be developed in the inertial range of wavenumbers of fluctuations (the Kolmogorov–Obukhov spectrum). From our model we suppose the power of the FBs is transformed partly into the energy of hydrodynamic turbulence in the envelope. If so, hydrodynamic turbulence may generate MHD fluctuations, which accelerate cosmic rays there and generate gamma-ray and radio emission from the FBs. We hope that this model may interpret the observed nonthermal emission from the bubbles. Full article

As a classic nonlinear filtering method, Spectral Amplitude Modulation (SAM) is widely used in the field of bearing fault characteristic frequency identification. However, when the vibration signal contains high-intensity noise interference, the accuracy of SAM in identifying fault characteristic frequencies is greatly reduced. To solve the above problems, a Data Enhancement Spectral Amplitude Modulation (DA-SAM) method is proposed. This method further processes the modified signal through improved wavelet transform (IWT), calculates its logarithmic maximum square envelope spectrum to replace the original square envelope spectrum, and finally completes SAM. By highlighting signal characteristics and strengthening feature information, interference information can be minimized, thereby improving the robustness of the SAM method. In this paper, this method is verified through fault data sets. The research results show that this method can effectively reduce the interference of noise on fault diagnosis, and the fault characteristic information obtained is clearer. The superiority of this method compared with the SAM method, Autogram method, and fast spectral kurtosis diagram method is proved. Full article

Multicarrier navigation modulation is a trend within next-generation global navigation satellite systems (GNSS) aiming to enhance navigation performance, but it forces amplifiers to work in nonsaturation zones, resulting in low power efficiency. This paper presents constant-envelope multiplexing (CEM) based on clipping to overcome the low transmission efficiency of orthogonal multi-binary offset carriers (OMBOCs). The clip constant-envelope OMBOC (CCE-OMBOC) features a hard limit for the original OMBOC signal, and its cross-correlation function (CCF) has a fixed ratio with the CCF of the original OMBOC. Thus, the clipping process has no adverse effect on navigation performance. Additionally, the expression of transmission and multiplexing efficiency is presented according to OMBOC’s amplitude distribution. A low sampling rate is suggested for the CCE-OMBOC, which reduces the cost of signal generation. For OMBOC, the CCE-OMBOC provides multiplexing efficiency comparable to that of constant-envelope multiplexing via intermodulation construction (CEMIC). CCE-OMBOC has a straightforward generation process; in contrast, the complexity of CEMIC rises significantly with increasing subcarriers. Moreover, the CCE-OMBOC is a multicarrier CEM modulation tool that has good tracking performance and excellent compatibility. The greater the number of subcarriers, the more navigation services and the higher the navigation data rate. The CCE-OMBOC can be used in next-generation GNSS and integrated communication and navigation systems. Full article

Bearings are the most vulnerable component in low-voltage induction motors from a maintenance standpoint. Vibration monitoring is the benchmark technique for identifying mechanical faults in rotating machinery, including the diagnosis of bearing defects. The study of different bearing fault phenomena under induction motor transient conditions offers interesting capabilities to enhance classic fault detection techniques. This study analyzes the low-frequency localized bearing fault signatures in both the inner and outer races during the start-up and steady-state operation of inverter-fed and line-started induction motors. For this aim, the classic vibration envelope spectrum technique is explored in the time–frequency domain by using a simple, resampling-free, Short Time Fourier Transform (STFT) and a band-pass filtering stage. The vibration data are acquired in the motor housing in the radial direction for different load points. In addition, two different localized defect sizes are considered to explore the influence of the defect width. The analysis of extracted low-frequency characteristic frequencies conducted in this study demonstrates the feasibility of detecting early-stage localized bearing defects in induction motors across various operating conditions and actuation modes. Full article

N-(2-hydroxyl) propyl-3-trimethyl ammonium chitosan chloride (HTCC), a quaternized chitosan derivative, has been shown to exhibit a broad spectrum of antimicrobial activity, especially against bacteria and enveloped viruses. Despite this, molecular docking studies showing its atomic-level mechanisms against these microorganisms are scarce. Here, for the first time, we employed molecular docking analyses to investigate the potential antibacterial activity of HTCC against Staphylococcus aureus and its antiviral activity against human immunodeficiency virus 1 (HIV-1). According to the findings, HTCC exhibited promising antibacterial activity with high binding affinities; however, it had limited antiviral activity. To validate these theoretical outcomes, experimental studies were conducted. Different derivatives of HTCC were synthesized and characterized using NMR, XRD, FTIR, and DLS. The in vitro assays validated the potent antibacterial efficacy of HTCC against S. aureus, whereas the antiviral studies did not show good antiviral activity. However, our research also revealed a promising avenue for further exploration of the antimicrobial activity of HTCC nanoparticles (NPs), since, thus far, no studies have been conducted to show the antiviral activity of HTCC NPs against HIV-1. The nanosized HTCC exhibited superior antiviral performance compared to the parent polymers, with complete (100%) inhibition of HIV-1 viral activity at the highest tested concentration (0.33 mg/mL). Full article

In marine electric propulsion systems (MEPS) driven by variable-frequency drives, motor current signals often exhibit complex modulation components, ambiguous spectra, and severe noise interference, rendering it challenging to extract fault-related modulation components. To address this issue, we propose a zero-crossing tacholess order tracking method based on motor current signals. This method utilizes zero-crossing estimation of the instantaneous frequency to perform angular resampling of stator current signals and demodulates the envelope spectrum to extract fault characteristic spectra, enabling the diagnosis of mechanical faults in MEPS. Given the synchronization of the synchronous motor speed with the inverter fundamental frequency, this method estimates instantaneous frequencies in the time domain without requiring integration or time–frequency representation, which is simple and computationally efficient. Data validation on a small-scale marine electric propulsion test platform demonstrates that the proposed method exhibits good robustness under variable-speed conditions and effectively detects imbalance faults caused by propeller breakages and gear faults resulting from bevel gear tooth defects. Therefore, the proposed method can be applied to diagnose faults in downstream mechanical equipment driven by motors. Full article

Bearing health is key for maintaining good performance and safety in rotating machinery. As the diagnosis of mechanical faults develops toward intelligence and automation, accurate and systematic fault diagnosis algorithms are imperative. Focusing on the diagnosis of rolling bearing failures, this study utilizes a sliding time window to extract essential data segments. A series of signal processing techniques, including filtering, amplitude–frequency analysis, Hilbert envelope analysis, and energy analysis, is applied to establish a comprehensive dataset. For extraction of the hidden properties of the data, the recurrence quantity spectrum is defined for the input of the neural network. The goal is to obtain a cleaner dataset with enhanced features. A convolution neural network is constructed. Different activation functions in the activation layer are compared for better fault diagnosis algorithms. The established feature matrices are specifically defined to accurately identify the subtlest defects of bearings, thereby facilitating early detection. The proposed procedure distinguishes various fault modes. As for the multidimensional complexities of fault signals, this study carries out a comprehensive comparison of energies, recurrence quantification, and amplitude–frequency characteristics of bearing fault detection to assess the accuracy, computational efficiency, and robustness of bearing fault diagnosis. The proposed method and bearing fault detection procedures have potential in practical applications. Full article

A novel vernier effect filter is designed utilizing two cascaded Mach–Zehnder interferometers (MZIs). Integrating the filter into an erbium-doped fiber laser (EDFL), the tunability of laser wavelength is achieved. Each MZI comprises two sequentially interconnected 3 dB optical couplers (OCs), where the incoming light is initially split into two arms at the first OC and subsequently recombined at the second OC. Interference occurs due to the optical path difference between these two beams. Notably, the two MZIs exhibit closely matched free spectral ranges (FSRs), leading to the formation of a broadened envelope in the superimposed spectrum. By delicately adjusting the optical path difference between the two arms of one MZI, a little drift of the interference spectrum is induced. This small amount of drift, in turn, triggers a significant movement of the envelope, giving rise to the so-called vernier effect. Integrating the vernier effect filter into an EDFL, the wavelength of the fiber laser can be tuned from 1542.56 nm to 1556.62 nm, with a tuning range of 14.06 nm. Furthermore, by employing a high-precision stepper motor, a remarkable tuning accuracy of 0.01 nm is attainable. The side mode suppression ratio of all wavelengths is above 55 dB. In comparison to reported tunable fiber lasers utilizing MZI filters, the proposed fiber laser in this study offers enhanced precision and a more user-friendly tuning process. Full article

Ultrasound B-scan images are traditionally formed from the envelope of the received radiofrequency echoes, but the image texture is dominated by granular speckle patterns. Longstanding efforts at speckle reduction and deconvolution have been developed to lessen the detrimental aspects of speckle. However, we now propose an alternative approach to estimation (and image rendering) of the underlying fine grain scattering density of tissues based on power law constraints. The key steps are a whitening of the spectrum of the received signal while conforming to the original envelope shape and statistics, followed by a power law filtering in accordance with the known scattering behavior of tissues. This multiple step approach results in a high-spatial-resolution map of scattering density that is constrained by the most important properties of scattering from tissues. Examples from in vivo liver scans are shown to illustrate the change in image properties from this framework. Full article

To increase the detection accuracy of soil structure and moisture content in reconstituted soils under complex conditions, this study utilizes a 400 MHz ground-penetrating radar (GPR) to examine a study area consisting of loess, sandy loam, red clay, and mixed soil. The research involves analyzing the single-channel waveforms and two-dimensional images of GPR, preprocessing the data, obtaining envelope information via amplitude envelope detection, and performing a Hilbert transformation. This study employs a least squares fitting approach to the instantaneous phase envelope to ascertain the thickness of various soil layers. By utilizing the average envelope amplitude (AEA) method, a correlation between the radar’s early signal amplitude envelope and the soil’s shallow dielectric constant is established to invert the moisture content of the soil. The analysis integrates soil structure and moisture distribution data to investigate soil structure characteristics and moisture content performance under diverse soil properties and depths. The findings indicate that the envelope detection method effectively identifies stratification boundaries across different soil types; the AEA method is particularly efficacious in inverting the moisture content of reconstituted soils up to 3 m deep, with an average relative error ranging from 2.81% to 7.41%. Notably, moisture content variations in stratified reconstituted soils are more pronounced than those in mixed soil areas, displaying a marked stepwise increase with depth. The moisture content trends in the vertical direction of the same soil profile are generally consistent. This research offers a novel approach to studying reconstituted soils under complex conditions, confirming the viability of the envelope detection and AEA methods for intricate soil investigations and broadening the application spectrum of GPR in soil studies. Full article

A Rectangular Dielectric Resonator Antenna (RDRA) design for mmWave-frequency-band MIMO metrics is proposed, with a compact, low-complexity, high-gain structure that is easy to fabricate and offers reduced inter–port isolation. The RDRA operates in the mmWave spectrum, featuring a compact size of 1.307${\lambda }_0$ × 1.307${\lambda }_0$, an impedance bandwidth of 6%, and a resonant frequency of 28 GHz, with a peak gain of 7 dBi. A four element MIMO system iteration was developed while maintaining the performance of the single element antenna. Additionally, a simple, low-complexity slot-etching technique was applied to achieve an average inter-port element isolation of 14 dB. The design also achieved a novel four-beam petal-splitting radiation pattern. The MIMO metrics, with an envelope correlation coefficient (ECC) of <0.5 and a diversity gain (DG) < 10, were successfully met. The simulated and measured results are in good agreement. Full article

To solve the separation of multi-source signals and detect their features from a single channel, a signal separation method using multi-constraint non-negative matrix factorization (NMF) is proposed. In view of the existing NMF algorithm not performing well in the underdetermined blind source separation, the β-divergence constraints and determinant constraints are introduced in the NMF algorithm, which can enhance local feature information and reduce redundant components by constraining the objective function. In addition, the Sine-bell window function is selected as the processing method for short-time Fourier transform (STFT), and it can preserve the overall feature distribution of the original signal. The original vibration signal is first transformed into time–frequency domain with the STFT, which describes the local characteristic of the signal from the time–frequency distribution. Then, the multi-constraint NMF is applied to reduce the dimensionality of the data and separate feature components in the low dimensional space. Meanwhile, the parameter WK is constructed to filter the reconstructed signal that recombined with the feature component in the time domain. Ultimately, the separated signals will be subjected to envelope spectrum analysis to detect fault features. The simulated and experimental results indicate the effectiveness of the proposed approach, which can realize the separation of multi-source signals and their fault diagnosis of bearings. In addition, it is also confirmed that the proposed method, juxtaposed with the NMF algorithm of the traditional objective function, is more applicable for compound fault diagnosis of the rotating machinery. Full article

A physical method for modeling the phase spectrum of earthquake ground motion is derived by defining relationships between the envelope delay and Fourier amplitude. In this method, two parameters with clear physical meanings, namely the median arrival time and strong shock duration, are introduced. These parameters provide a logical basis for modeling the phase spectrum in a physical sense. A simulation method for earthquake ground motions is introduced, based on a physical amplitude model and the proposed method for modeling the phase spectrum. To investigate the physical meaning of the phase spectrum of earthquake ground motion and to be used for simulating earthquake ground motions, two techniques based on the discrete Fourier transform (DFT) and the continuous Fourier transform (CFT) are employed to calculate the envelope delay. It is demonstrated that when using the DFT, the range of envelope delays is dependent on the duration of the earthquake ground motion, and the range of envelope delays corresponding to peak amplitudes is dependent on the time span of the strong shock in ground motions. This dependency is not observed with the CFT. The proposed simulation method for earthquake ground motions was used to regenerate two recorded earthquake acceleration time histories. Numerical results demonstrate that this method can accurately reproduce the main characteristics of strong earthquake ground motion recordings. Full article