Spectral Density Distribution Research Articles

Sample entropy-based quantitative assessment of the arc magnetic field spectrum for improved arc welding quality

Arc magnetic field analysis is a valuable approach for assessing the stability of the arc welding process, yet existing methods lack the ability to effectively quantify the disorder within the process. Through an investigation into the characteristics of the arc magnetic field signal, it was observed that the occurrence of low-frequency random fluctuations in arc magnetic field power, induced by unstable factors such as bubbles or short circuits, contributed to increased complexity and randomness in the arc magnetic field signals. To visualise the arc magnetic field signals in a time-frequency domain, a spectrogram was employed, revealing a strong correlation between the distribution of maximum power spectral density (PSD) in the spectrogram and the stability of the arc welding process. Furthermore, a novel method based on sample entropy was introduced to provide a quantitative measure of this relationship. A comprehensive quantitative assessment indicator called arc magnetic field sample entropy (AMFSE) was proposed. This indicator effectively mitigates the influence of varying parameters on the quantitative results, enabling a more accurate and consistent representation of the stability of the arc welding process. The proposed method was validated through testing, yielding an accuracy rate exceeding 90%.

Statistical Properties of Exohiss Waves and Associated Scattering Losses of Radiation Belt Electrons

AbstractExohiss waves are a type of structureless whistler‐mode waves that exist in the low density plasmatrough outside the plasmapause and may potentially perturb the motions of electrons in the radiation belt and ring current. Using data from Van Allen Probe A, we analyze the distribution of magnetic power spectral density (PSD) of exohiss waves in different magnetic local time (MLT) and L‐shell regions near the geomagnetic equator. The results reveal that the peak magnetic PSD of exohiss waves is the weakest at MLT = 0–6 and the strongest at MLT = 12–18. The magnetic PSDs of exohiss waves are much lower than those of chorus and hiss waves except for the MLT = 12–18 sector. In addition, we calculated the quasi‐linear bounce‐averaged pitch angle and momentum diffusion coefficients (〈Dαα〉 and 〈Dpp〉) of electrons caused by exohiss waves. The diffusion coefficients are then compared with those caused by chorus and hiss waves. The peak 〈Dαα〉 of electrons driven by exohiss waves becomes stronger as L‐shell increases at all MLTs and is the greatest on the dayside, especially in the sector of MLT = 12–18. Exohiss waves have more significant effect on the loss of radiation belt electrons with specific energy levels related to MLT and L‐shell region compared to chorus and hiss waves. On the other hand, 〈Dpp〉 of electrons caused by exohiss waves is very small, which illustrates that exohiss waves have almost no acceleration effect on electrons.

Numerical vibrational acoustics and sound quality assessment of pipa strings

This study harmonizes subjective auditory and psychological elements related to plucked strings with objective physical attributes through spectrum analysis and numerical simulation, confirming the congruity between objective assessment systems and subjective perceptions in evaluating pipa string sound quality. The research combines experimental investigation of plucked pipa string vibrations with detailed numerical simulations of vibrational acoustic fields using a specified 3 N input force. Results demonstrate that as frequency increases (from A4: 440 Hz to E6: 1320 Hz), more pronounced vibrations emerge along the pipa body, leading to heightened overall sound pressure within the vibrational acoustic fields. The sound pressure distribution analysis reveals that the rosewood pipa exhibits significantly lower standard deviations of 41.8% and 41.9% compared to the tung wood pipa, and 24.6% and 32.2% lower than the white wood pipa at 440 Hz and 1320 Hz, respectively, highlighting the rosewood pipa’s superior sound pressure uniformity. Additionally, an assessment of the A4 signal’s Power Spectral Density (PSD) distribution underscores even spectral energy dispersion in the rosewood pipa’s A4 sound signal, with minor resonance peaks in higher-order overtones beyond 5000 Hz, further substantiating the superior sound quality of the rosewood pipa, in line with expert reviews.

Specular transformation of electromagnetic partially coherent beams with a wave-folding interferometer

We consider a class of specular or anti-specular vector beams, by illuminating stochastic vector beams into a prism-based wavefront-folding interferometer. Such transform is applied to various genuine model input beams, and then the properties of the resulting fields are discussed. Numerical results show that the specular nature of these vector fields not only creates sharp internal spectral density distribution, but also produces novel polarization patterns with oscillations or a central dip on the degree of polarization-profile. Such optical characteristics can be flexibly modulated by the correlation structure of the source. We also suggest that the specular transform could be efficiently employed in developing novel partially coherent vector beams.

Masses of the conjectured H-dibaryon at different temperatures*

Abstract We present a lattice QCD determination of masses of the conjectured H-dibaryon, denoted as , at nine different temperatures: 0.24, 0.63, 0.76, 0.84, 0.95, 1.09, 1.27, 1.52, and 1.90. The masses of baryons N, Σ, Ξ, and Λ at different temperatures were also computed. The simulations were performed on an anisotropic lattice with flavours of clover fermion at a quark mass corresponding to . The thermal ensembles were provided by the FASTSUM collaboration, whereas the zero temperature ensembles were provided by the Hadspec collaboration. We also calculated the spectral density of the correlation function of those particles. The spectral density distributions show a rich peak structure at the lowest temperature; at intermediate temperatures, the mass values of those particles obtained by the extrapolation method reflect a two-peak structure. While the spectral density for the octet baryon becomes smooth at 1.27, 1.52, and 1.90, the spectral density for the H-dibaryon becomes smooth at . At , the mass difference of the H-dibaryon and Λ pair, expressed as , was estimated to be MeV, which suggests the existence of a bound H-dibaryon state.

Data-driven prediction of aerodynamic noise of transonic buffeting over an airfoil

Accurately predicting buffet frequency and aerodynamic noise level is crucial in transonic buffet noise reduction studies. In this study, the Random Forest (RF) algorithm is employed to predict the Power Spectral Density (PSD) and Overall Sound Pressure Level (OASPL) distribution over the supercritical airfoil RAE2822. The study indicates that the RF algorithm exhibits greater advantages over the Multi-Layer Perceptron (MLP). This algorithm does not suffer from the problems of high-frequency divergence or inflection distortion, maintaining a reduction in prediction errors for OASPL and PSD by approximately three to four orders of magnitude. Additionally, this paper proposes a priori criterion for evaluating the accuracy of PSD prediction. When there is a strong correlation between PSD at adjacent points, a data-driven modeling approach can achieve higher prediction accuracy. However, when the root mean square error of the cross-correlation functions, auto-correlation functions, and the PSD between adjacent points are both high, the generalization ability of pure data-driven modeling is insufficient, necessitating the additional monitoring points to ensure prediction accuracy.

Numerical Characterization of Prestall Disturbances in a Compressor Stage

Abstract Compared to the subject of rotating stall, less attention has been given to prestall flow disturbances in turbomachinery. This is mostly due to the fact that these phenomena, often referred to as Rotating Instabilities, do not necessarily or distinctly occur in every compressor and usually last for a long period without posing serious threats to stable operation. The present study aims at numerically characterizing prestall disturbances in detail in a compressor stage in which they have been experimentally observed. Full-annulus computational fluid dynamics (CFD) computations employing a hybrid scale-resolving turbulence model are performed and compared against unsteady experimental data. Assessment of specific prestall disturbance metrics, including power spectral density, coherence, and circumferential mode distribution at the rotor clearance, shows that the numerical model is successful in reproducing the unsteady phenomena close to stall inception. Moreover, dynamic mode decomposition is employed to directly link each peak of the unique prestall disturbance spectral signature to spatial structures with a different circumferential order. This procedure is done for both 1D circumferential modes, based on flush-mounted pressure probes, and for 2D surfaces exposing the tip clearance dynamics. The high-resolution numerical model, supplemented with vortex identification criteria and data-driven decompositions, enhances the understanding of prestall disturbances and their associated coherent flow structures.

Transient quasi-periodic oscillations in the gamma-ray light curves of bright blazars

ABSTRACT Transient quasi-periodic oscillations (QPOs) are extremely interesting observational phenomena. However, the precise physical mechanisms leading to their generation are still hotly debated. We performed a systematic search for transient QPO signals using Weighted Wavelet Z-transforms on the gamma-ray light curves of 134 bright blazars with peak flux exceeding 1 × 10−6 ph cm−2 s−1 as monitored by Fermi-LAT. Artificial light curves were generated from the power spectral density and probability distribution functions of the original light curves to assess the significance level of transient QPO. We discuss several physical mechanisms that produce transient QPOs, with the helical jet model providing the best explanation. This study identified four new transient QPO events. Interestingly, repetitive transient QPOs are observed in PKS 0537-441, and nested transient QPOs are detected in PKS 1424−41. Additionally, we find that transient QPOs tend to occur in the flare state of the blazar. Finally, we estimate the incidence of transient QPO events to be only about 3 per cent.

Variable-Angle Random High-Frequency Voltage Injection Strategy with Cross-Saturation Effect Compensation for Sensorless Synchronous Reluctance Motor Drives

There are usually noise problems when the position sensorless control of a synchronous reluctance motor (SynRM) is carried out by high-frequency (HF) signal injection method. Due to the special structure, the cross-saturation effect of the SynRM is particularly serious, resulting in reduced position observation accuracy. In this paper, a variable-angle random HF voltage injection strategy with cross-saturation effect compensation is proposed for position sensorless SynRM drives. Random number generation based on the chaotic mapping method is used to generate random HF voltage signals with different frequencies for injection; the current power spectral density (PSD) distribution is extended and the HF noise can be reduced. A control strategy based on variable-angle square-wave injection is proposed to suppress the cross-saturation effect. By measuring the position error curves of different loads off-line and polynomial fitting the curves, the position error is achieved by combining with the corresponding signal demodulation algorithm. The proposed method does not require additional hardware resources and can maintain high control accuracy and robustness. Finally, the effectiveness of the proposed sensorless control strategy is verified on a 3 kW SynRM experimental platform.

Noninvasive EEG measurement of sleep in the family cat and comparison with the dog

Abstract We have successfully measured the sleep electroencephalogram (EEG) of 12 family cats during an afternoon nap using a completely noninvasive methodology originally developed and validated for family dogs. Extracting both macrostructural and spectral sleep variables from the acquired data, we: (1) provided a descriptive analysis of sleep structure in cats and the power spectral density (PSD) distribution considering 3 sleep stages—drowsiness, non-rapid eye movement (NREM), and rapid eye movement (REM) sleep; and (2) compared the results to those obtained in family dogs measured under the same conditions and using the same methodology. Importantly, our description of sleep structure and PSD distribution in cats proved to be comparable to those of earlier invasive studies, highlighting that appropriate noninvasive methodologies may provide a viable alternative to those that are invasive in some cases. While no macrostructural differences were found between the sleep of cats and dogs, and the characteristic PSDs were mostly similar across sleep stages within the 2 species, the high-frequency resolution comparison of PSD distributions revealed differences between the 2 species in all sleep stages (concerning the delta, theta, alpha, sigma, and beta bands in drowsiness and NREM sleep; and the delta, alpha, and sigma bands in REM sleep). Potential factors underlying these differences are discussed, including differences in circadian rhythms, sleep homeostatic regulation, experienced stress, or even differential attitudes toward owners—highlighting important links between sleep characteristics and often more complex neural and behavioral features.

Observation of the dynamic evolution process of vacuum arc microscopic particles based on the emission spectrum principle

The distribution of microscopic particles directly affects the recovery of the post arc insulating medium and determines whether the fault current can be interrupted. Based on the principle of vacuum arc emission spectrum, a high-speed spectrum observation platform was built to study the distribution of microscopic particles during the arc burning, and the axial and radial spectral line intensity and density distributions of atoms and ions under different current amplitudes were obtained. The results show that the CuI spectral line intensity has two peaks near the cathode and anode, while in the arc column it is relatively low. The peak of the CuI spectral line intensity near the electrode is caused by electrode evaporation. The peak duration of the CuI spectral line intensity near the cathode is always longer than that near the anode. The CuII spectral line intensity is lower, appears later and disappears earlier, which in the arc column increased obviously, compared with CuI. The CuII density near the cathode is higher than that near the anode, and the CuII density in the arc column is higher than in the two electrodes, which is similar to the axial distribution of electron density. The radial distribution curve of CuI and CuII density is similar to the radial distribution curve of spectral line intensity, and displays the characteristics of a high center and low edge in the radial direction of the arc gap. The difference is that the width of the atomic spectral line is larger than that of the corresponding ionic spectral line, the distribution curve of the ionic spectral line is smooth and symmetrical, and the radial attenuation rate of the CuII density is larger than that of the corresponding CuI. This reflects the ionization of atoms and the effect of magnetic fields. The radial and axial distribution of the particle density is opposite to that of the excitation temperature. Electrode emission will first affect the atom formation.

Asphalt Pavement Transverse Cracking Detection Based on Vehicle Dynamic Response

Transverse cracking is thought of as the typical distress of asphalt pavements. A faster detection technique can provide pavement performance information for maintenance administrations. This paper proposes a novel vehicle-vibration-based method for transverse cracking detection. A theoretical model of a vehicle-cracked pavement vibration system was constructed using the d’Alembert principle. A testing system installed with a vibration sensor was put in and applied to a testing road. Then, parameter optimization of the Short-time Fourier transform (STFT) was conducted. Transverse cracking and normal sections were processed by the optimized STFT algorithm, generating two ideal indicators. The maximum power spectral density and the relative power spectral density, which were extracted from 3D time–frequency maps, performed well. It was found that the power spectral density caused by transverse cracks was above 100 dB/Hz. The power spectral density at normal sections was below 80 dB/Hz. The distribution of the power spectral density for the cracked sections is more discrete than for normal sections. The classification model based on the above two indicators had an accuracy, true positive rate, and false positive rate of 94.96%, 92.86%, and 4.80%, respectively. The proposed vehicle-vibration-based method is capable of accurately detecting pavement transverse cracking.

A data-driven network decomposition of the temporal, spatial, and spectral dynamics underpinning visual-verbal working memory processes

The brain dynamics underlying working memory (WM) unroll via transient frequency-specific large-scale brain networks. This multidimensionality (time, space, and frequency) challenges traditional analyses. Through an unsupervised technique, the time delay embedded-hidden Markov model (TDE-HMM), we pursue a functional network analysis of magnetoencephalographic data from 38 healthy subjects acquired during an n-back task. Here we show that this model inferred task-specific networks with unique temporal (activation), spectral (phase-coupling connections), and spatial (power spectral density distribution) profiles. A theta frontoparietal network exerts attentional control and encodes the stimulus, an alpha temporo-occipital network rehearses the verbal information, and a broad-band frontoparietal network with a P300-like temporal profile leads the retrieval process and motor response. Therefore, this work provides a unified and integrated description of the multidimensional working memory dynamics that can be interpreted within the neuropsychological multi-component model of WM, improving the overall neurophysiological and neuropsychological comprehension of WM functioning.

A novel mechanism of turbulent kinetic energy harvesting by horizontal-axis wind and hydrokinetic turbines

We present a study on the influence of the turbulence generated by a cylinder on the performance of a free horizontal-axis turbine. The analysis focuses on the power coefficient, flow characteristics, and Turbulence Kinetic Energy (TKE) spectral density distribution. The mean velocity, turbulence intensity, and TKE are evaluated in the upstream and downstream planes of the turbine for configurations with and without the upstream cylinder. The results show that the power coefficient exhibits a peak when the rotor rotation frequency coincides with the frequency of vortex shedding from the cylinder, indicating a mechanism of conversion of TKE carried by large-scale structures into mechanical power. It was also observed that the turbine generates downstream turbulence in the absence of the cylinder but reduces the downstream turbulence when the cylinder is present. Spectral analysis of TKE confirms the influence of the frequency of vortex shedding on the velocity recovery of the turbine wake. The main contribution of this paper is the identification of a new mechanism of conversion of the TKE contained in large coherent turbulent structures into mechanical power. This study provides a further understanding of the complex phenomena involved in the interaction between the turbine and the upstream turbulent flow.

An experimental investigation on the thermal behavior of synthetic jets involving non-circular orifices with varying wave patterns

ABSTRACT The present work reports the thermal behavior of synthetic jets (SJs) with different non-circular orifices and various waveforms such as triangular, sinusoidal, and square. Tests are conducted for the different nozzle-to-plate spacing (1–25) for a given value of Reynolds number (5380). The triangular waveform exhibits better heat transfer for all the orifice shapes. The value of maximum heat transfer for rectangular SJ is found to be 32% and 16.5% higher than isosceles and equilateral triangular SJs, respectively. The equilateral triangular SJ exhibits 12.9% higher heat transfer than the isosceles triangular SJ. The power spectral density distribution is plotted for all three waveforms.

Dynamic Detection of Vigorous Worm in Infected Host

The Internet has developed to give many benefits to mankind. The access to information being one of the most important. Worms cause major security threats to the Internet. Worms are software components that are capable of infecting a computer and then using that computer to infect another computer. The cycle is repeated, and the population of worm-infected computers grows rapidly. Smart worms cause most important security threats to the Internet. The ability of smart worms spread in an automated fashion and can flood the internet in a very short time. A new class of smart worms, referred to as Camouflaging worm (C-Worm in short). C-worm is different from traditional worm. C-worm intelligently manipulate its scan traffic volume over time. Motivated by observations, we designed a novel Spectrum Based detection Scheme to detect the C-worm. This scheme uses Power Spectral Density (PSD) distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C-worm traffic from background traffic. This scheme is effectively detecting not only the C-worm but traditional worms as well. The goal is to prevent, detect and delete the smart worms as well as traditional worms.

Vibration Response Law of Aircraft Taxiing under Random Roughness Excitation

Understanding the vibration response patterns of aircraft taxiing under runway roughness excitation is crucial for aircraft design and runway performance evaluation. In this paper, we establish pavement roughness models for both asphalt and concrete surfaces, taking into account their unique structural characteristics. We construct a six-degrees-of-freedom aircraft model using multi-rigid-body system dynamics theory and employ the pseudo-excitation method to examine the influence of pavement roughness types on the steady vibration response of aircraft taxiing at constant speeds. Furthermore, we analyze the non-stationary vibration response patterns of aircraft during takeoff and landing taxiing using the method of instantaneous frequency response function with space frequency. Lastly, we explore the effect of stochastic structural parameters on aircraft vibration response using the Monte Carlo method. Our findings reveal that the roughness power spectrum differs between asphalt and concrete pavements, and the established roughness models in this paper demonstrate a strong fit (R2 > 0.95). The type of pavement roughness has a relatively minor impact on the power spectral density distribution of the aircraft vibration response, suggesting that the same roughness model can be used for both asphalt and concrete pavements when high accuracy is not required. The power spectral density distribution of aircraft vibration response varies across different motion attitudes, with the vibration response during landing being significantly larger than that during takeoff. Among the aircraft structural parameters, the randomness of the sprung mass has the most substantial effect on the aircraft vibration response, potentially causing the variation coefficient of dynamic load on the front landing gear to exceed 0.11. Tire stiffness comes next, which can lead to the variation coefficient of dynamic load on the main landing gear reaching 0.07. The results have a guiding role in optimizing aircraft structure design and ensuring pavement performance.

Scattering of radially polarized partially coherent vortex beams from a random medium with semi-hard boundary

In this paper, scattering medium with a semi-hard boundary is extended to the case of a quasi-homogeneous random medium for the first time. Applying the first-order Born approximation, far-field distribution of radially polarized partially coherent vortex beams scattered upon the random medium with semi-hard boundary is studied. Spectral density distribution, degree of spectral polarization, polarization angle, and degree of ellipticity of the scattering field in the far zone are investigated. Influence of characteristics of the incident beam and scattering medium on the far-zone scattering field are discussed. In addition, phase singularity of the scattering field’s center is also described. It is interesting to find that the far-field scattering field is circularly polarized with a Gaussian distribution, though the incident field is radially polarized with a dark-hollow distribution. The center of the scattering field is completely polarized, while on the edge of the scattering field, degree of polarization shows obvious fluctuations with the change of parameters of the incident beam and medium. Results obtained here could find application in the acquisition of medium structure information.

Experimental on the fatigue failure areas of wind turbine blades’ rotating fundamental frequency

The dominant type of vibration in wind turbine blades is flapwise vibration, which causes fatigue loading owing to the out-of-plane alternating load, with blade breakage occurring when the load is below the strength limit. Consequently, the mechanism and distribution of alternating-load generation must be understood to reduce the fatigue load. The strain data in the flapwise direction at the characteristic position of the operating wind turbine were collected to learn the characteristics of the spanwise distribution of the strain power spectral density (PSD) amplitude, to explore the fatigue damage-prone area and the generation mechanism, and to reveal the influence of the rotational speed on the spanwise distribution of the strain. It was evident that linked torsional and edgewise vibrations were predominant and that the strain PSD amplitude of the 1P loading component was nonlinear because of the Brazier effect in the transition region. The fatigue failure susceptible region of the rotating blade is more accurately identified. Except for the 0.10 R position, the blade 1P component 0.70–0.75 R spanwise region is more prone to failure. The rotation speed increases the dynamic fluctuation of spanwise strain.

Random Telegraph Noise in Analog CMOS Circuits

Flicker noise, or 1/f noise, is known to increase as devices scale down. However, as the scaling of MOS transistors advances, the effect of individual oxide defects, which originates flicker noise, becomes apparent through distinguishable discrete fluctuation in current. In such cases, flicker noise is recognizable as random telegraph noise (RTN). Another typical characteristic of RTN is that seemingly identical devices have different noise characteristics, as RTN variability from device to device also increases with scaling. Due to the large variability of RTN in highly-scaled devices, circuit yield must be evaluated during noise analysis. This work proposes a model to analyze the effect of RTN in analog circuits and to evaluate circuit yield. The model can be used in the traditional workflow of noise analysis. The model estimates the distribution of RTN power from the distribution of the noise spectral density. Then, quantiles from the power distribution are used for predicting current/voltage fluctuations for a given yield. This work shows how to use the proposed model to calculate random decision errors in comparators, jitter in oscillators and phase-locked loops, and the impact of RTN in correlated double sampling circuits.