Fourier Transform Power Spectra Research Articles

A Denoising Method of Partial Discharge Signal Based on Improved SVD-VMD

A denoising method combined with singular value decomposition (SVD) and Variational mode decomposition (VMD) is proposed to eliminate noise in on-site partial discharge (PD) signals from high-voltage electrical equipment. In the Fourier transform power spectrum, periodic narrowband interference was eliminated after SVD was offered to determine the number of singular values of periodic narrowband interference. Then, the PD signal was decomposed into K intrinsic mode function components by VMD. The empirical mode decomposition method was used to determine the K value of white noise’s intrinsic mode function components. An improved 3σ criterion threshold method was proposed to eliminate the residual noise in the PD signal. The denoising method was compared with the other two methods to analyze the denoising effect on the simulation and experimental PD signal. This paper’s denoising method can eliminate periodic narrowband interference and white noise in different PD signals of cavity discharge, corona discharge, and those from the motors’ coil. The denoised PD pulse waveform has a higher signal-to-noise ratio and normalized correlation coefficient and a lower mean square error, indicating that the waveform’s original characteristic remains.

A novel moving window-based power spectrum features for single-channel EEG classification using machine learning

Electroencephalogram (EEG) signal classification is a crucial and very difficult task. Meanwhile, extracting features that are representative and able to discriminate different types of EEG signals is a complex task. Such features are usually fed to machine learning algorithms to classify the EEG signals based on the extracted features. This paper proposed a highly accurate and real-time features extraction method that can be used to help physicians in detecting different types of seizures and states in EEG signals characterized by a set of features extracted from the power spectrum of the EEG window. This is achieved by applying the following four steps. First, the EEG signals dataset contains different classes of EEG signals: Normal Eye Closed, Normal Eye Opened, Focal Seizure, Non-Focal Seizure, and Ictal Seizure activities. Second, each EEG signal has a length of 4097 samples sampled with a sampling frequency of 173.6 Hz which resulted in 23.6 seconds in length, this signal will be truncated into windows (Sub-signals) with a length of 349 samples (Approximately 2 seconds) with a total number of 12 windows for each signal. Afterward, the Fourier Transform (FT) based power spectrum will be computed for each window, then a set of different features are extracted from each window's FT power spectrum, and these features are classified using different Machine Learning (ML) algorithms. The results showed that the proposed methodology yields around 98% accuracy for the five different classification scenarios using different ML algorithms. The suggested method is hence robust, fast, real-time, accurate, and simple.

Vertical Conductivity and Topography in Electrostrictive Germanium Sulfide Microribbon via Conductive Atomic Force Microscopy.

Layered group IV monochalcogenides are two-dimensional (2D) semiconducting materials with unique crystal structures and novel physical properties. Here, we report the growth of single crystalline GeS microribbons using the chemical vapor transport process. By using conductive atomic force microscopy, we demonstrated that the conductive behavior in the vertical direction was mainly affected by the Schottky barriers between GeS and both electrodes. Furthermore, we found that the topographic and current heterogeneities were significantly different with and without illumination. The topographic deformation and current enhancement were also predicted by our density functional theory (DFT)-based calculations. Their local spatial correlation between the topographic height and current was established. By virtue of 2D fast Fourier transform power spectra, we constructed the holistic spatial correlation between the topographic and current heterogeneity that indicated the diminished correlation with illumination. These findings on layered GeS microribbons provide insights into the conductive and topographic behaviors in 2D materials.

Topography dependence of conductivity in electrostrictive germanium sulfide nanoribbons

Layered group IV monochalcogenides have garnered considerable attention as a new class of two-dimensional (2D) semiconducting materials owing to their unique crystal structure and novel physical properties. The present work describes the chemical vapor transport synthesis of single-crystalline GeS nanoribbons. The findings demonstrate that with incrementally applied voltage, electrostrictive deformation and highly vertical current occur more significantly. Additionally, using a 2D fast Fourier transform power spectra, we demonstrate that the horizontal distribution of topography and current is more inhomogeneous than the vertical distribution, and that their monolithic spatial correlation weakens with increasing applied voltage. Moreover, we discovered that electrostrictive deformation has a sizable effect on the monolithic vertical resistance. Furthermore, local hollow positions are more conductive than bulge positions, as demonstrated by the ‘resistor’ model and local current–voltage curve. These findings on layered GeS nanoribbons not only shed light on the topographic and electrical properties of the material but also expand the possibilities for other nanoscale electronic and electromechanical device applications.

Preliminary study of articulatory characteristics in open bite subjects revealed by 3T magnetic resonance imaging movies

Objectives: Previous studies have reported that articulatory dysfunction accompanied by a certain type of malocclusion can be improved by orthodontic treatment. We developed a 3-T magnetic resonance imaging (MRI) movie method with tooth visualization that can display the dynamic movement of articulation without radiation exposure. To the best of our knowledge, there is currently no report on the possible differences in articulatory movement between subjects with a normal occlusion and those with malocclusion using the 3T MRI movie method. Thus, the objective of this study was to examine the articulatory difference between subjects with a normal occlusion and those with an open bite using an MRI movie. Materials and Methods: Twenty healthy adult females, ten with a normal occlusion and ten with an anterior open bite were recruited. The overbite of the open bite subjects was zero or smaller, and all of them exhibited a tongue-thrusting habit during swallowing. A turbo spin echo image with a contrast medium was used to visualize the anterior teeth, and articulatory movement during articulation of the vowel-consonant-vowel syllable (/asa/) was scanned. The difference in tongue movement between subjects with a normal occlusion and those with an open bite was compared by measuring seven variables. Moreover, the distance between the incisal edge and the tongue apex during articulation of /s/ and the speech duration were compared. Furthermore, frequency analysis on /s/ by fast Fourier transform power spectrum was performed. Results: The tongue apex of the open bite subjects moved more anteriorly than that of the normal subjects. However, there was no significant difference in the phonetic analysis between subjects with a normal occlusion and those with an open bite. Conclusion: The 3-T MRI movie was an efficient method to quantify articulatory tongue movements. Although there was a difference in tongue movement during swallowing between subjects with a normal occlusion and those with an open bite, the difference in the articulatory tongue movements was minimal, suggesting it could be a functional compensation.

Health Analysis of Transformer Winding Insulation Through Thermal Monitoring and Fast Fourier Transform (FFT) Power Spectrum

This paper presents a health analysis technique for transformer winding insulation through thermal monitoring and Fast Fourier Transform (FFT) power spectrum. A novel thermal model for the Kraft paper insulation of transformer is proposed by using the transformer’s top-oil and winding hot-spot temperature models. The relationship between the temperature rise of oil inside the transformer tank and the winding insulation degradation are considered by utilizing the data-sets and daily load cycles of a 10/13 MVA, 132/11 kV, 50 Hz, ONAF grid power transformer. The model based on IEEE Guide for loading mineral-oil-immersed transformers is developed in Simulink. The hotspot temperature rise from the thermal model is used as a reference to analyze the winding insulation degradation in the form of high frequency partial discharges (PDs) upon the output parameters of the transformer. Using data analysis techniques, a correlation is presented between the load cycles and the hot-spot temperature through which the health status of the transformer winding insulation is estimated. Moreover, the high frequency transients were detected using the Fast Fourier Transform (FFT) spectrum analyzer tool in MATLAB. The preliminary study shows that high frequency PDs are detected for the overheated and deteriorated state of the winding insulation. The results show that the proposed technique is feasible for the health analysis of power transformers and successfully predicted the deterioration of the transformer winding insulation.

Spin wave modes of nanoellipses with a magnetic radial vortex configuration

Radial vortices are exotic magnetic configurations that have several potential applications in Spintronics. In this paper, using micromagnetic simulation, we have proved that magnetic radial vortices can also be found in elliptic nanostructures, and have obtained the frequencies of their spin wave modes as a function of the sizes and ellipticity of the structures (here, we have defined the ellipticity as the ratio of the major axis to the minor axis D=Dx/Dy). Our results show that the size of the core of the magnetic radial vortex is not dependent on D. We have also obtained the spatial distribution of Fourier transform power spectra of the spin wave modes. Our results show that the variation in the values of D leads to the emergence of new spin wave modes, and that in general, the increase in the values of D leads to a decrease in the values of the frequencies of the spin wave modes.

Single-shot coherent power-spectrum imaging of objects hidden by opaque scattering media.

We report coherent imaging of objects behind opaque scattering media with only one piece of the power spectrum pattern. We solve the unique solution and improve algorithm speed for the inverse problem. Based on the proposed scattering-disturbance model, with only one piece of the Fourier transform power spectrum pattern under coherent illumination, we successfully reconstruct clear images of the objects fully hidden by an opaque diffuser. The experimental results demonstrate the feasibility of the reconstruction method and the scattering-disturbance model. Our method makes it possible to carry out snapshot coherent imaging of the objects obscured by scattering media, which extends the methodology of x-ray crystallography to visible-light scattering imaging for underwater and living biomedical imaging.

Electrospray ionization-ion mobility spectrometry-high resolution tandem mass spectrometry with collision-induced charge stripping for the analysis of highly multiply charged intact polymers.

Polymers with large molecular weight are difficult to interpret using electrospray ionization-mass spectrometry (ESI-MS) due to the generation of various highly multiply charged analytes. Although ESI-ion mobility spectrometry (IMS)-MS is effective in reducing the complexity of the mass spectrum, this approach is insufficient for analyzing highly multiply charged polymers. In this study, we propose a method combining tandem mass spectrometry (quadrupole and high-resolution time-of-flight MS, QMS/TOFMS), IMS, and collision-induced charge stripping (CICS) for analyzing large intact polymers (∼40 kDa), which are highly multiply charged. The number of charges can be estimated from a Fourier transform power spectrum of a mass spectrum when the charge number is less than approximately 20. Interpretations of the spectra of poly(ethylene oxide)s (PEOs) weighing 20 kDa, poly(methyl methacrylate)s weighing 22 kDa, and methoxy-PEO-maleimide weighing 40 kDa were successfully demonstrated with isotope level and polymerization degree level separations, respectively. In the proposed method, a mixture can be analyzed for relatively small (a few kDa) and large (a few tens of kDa) polymers simultaneously without any sample pretreatment.

Correlating new directional measures of myelin and axonal integrity in T2-weighted MRI with quantitative histology in multiple sclerosis

BackgroundImaging measurement of structure alignment has shown increasing importance in determining tissue properties. It is not known if a similar ability for characterizing neuropathology exists. New methodsThis study aimed to validate a new alignment-assessing method for measuring myelin and axonal properties using quantitative histological metrics. The new method involved analysis of the Fourier transform (FT) power spectrum in standard magnetic resonance imaging (MRI). T2-weighted MRI were collected from 10 post-mortem multiple sclerosis (MS) brain samples. Three tissue types were examined: lesions, diffusely abnormal white matter, and normal appearing white matter. MRI analysis included computing the FT power spectrum; extracting alignment histograms; and calculating dominant orientation and alignment complexity (angular entropy). Post MRI, the brain samples were processed for myelin and axonal staining, and the stained images were used to derive quantitative orientation measures using structure tensor analysis for MRI comparison. ResultsThere were significant differences in orientation metrics between tissue types in both MRI and histology, and MRI measurements correlated strongly with histological indices. Moreover, the joint effect of myelin and axonal entropy explained over 95% of the variance of MRI angular entropy. Comparison with existing methodThere is no established method for characterizing myelin and axonal pathology using standard MRI. Advanced MRI methods have the potential to do this but are still in research development and are not yet routinely acquired in clinical practice. ConclusionsAlignment measurement using clinical MRI scans may become a valuable new method for characterizing myelin and axonal properties in MS patients.

Long-term effects of vestibular rehabilitation and head-mounted gaming task procedure in unilateral vestibular hypofunction: a 12-month follow-up of a randomized controlled trial

Objective: To investigate the long-term effects of adding virtual reality–based home exercises to vestibular rehabilitation in people with unilateral vestibular hypofunction. Design: Follow-up otoneurological examination in two randomized groups following a previous one-month trial. Setting: Tertiary rehabilitation center. Subjects: A total of 47 patients with unilateral vestibular hypofunction, one group (n = 24) undergoing conventional vestibular rehabilitation and the other one (n = 23) implementing, in addition, head-mounted gaming home exercises, 20 minutes per day for one month. Interventions: One year after completing rehabilitation, patients underwent testing with static posturography, video head impulse test, self-report questionnaires, and a performance measure. Main measures: Vestibulo-ocular reflex gain, posturographic parameters such as length, surface, and fast Fourier transform power spectra, self-report, and gait performance measure scores. Results: Vestibulo-ocular reflex gain was significantly better with respect to pretreatment in both groups. The mixed-method group showed significantly higher gain scores: mean (standard deviation (SD)) at 12 months was 0.71 (0.04), versus 0.64 (0.03) for the vestibular rehabilitation–only group (P < 0.001). Accordingly, some classical posturography scores such as surface with eyes open and length with eyes closed and low-frequency power spectra were significantly different between groups, with the virtual reality group showing improvement (P < 0.001). Self-report measures were significantly better in both groups compared to pretreatment, with significant improvement in the mixed-method group as compared to conventional rehabilitation alone: Dizziness Handicap Inventory mean total score was 24.34 (2.8) versus 35.73 (5.88) with a P-value <0.001. Conclusion: Results suggest that head-mounted gaming home exercises are a viable, effective, additional measure to improve long-term vestibular rehabilitation outcomes.

Fast Fourier Transform power spectrum of radon activity

Measurement of outdoor Radon‑222 ( 222Rn) activity at National Atmospheric Research Laboratory (NARL), Gadanki, India, is carried out using Alpha GUARD PQ 2000 PRO from October 2011 to July 2014 and analyzed. The general inspection of time series reveals the decomposition of periodicity, significant diurnal and seasonal trend, and correlation between the measured and dependent variables. Detailed analyses have revealed that the Fast Fourier transform power spectrum of 222Rn has several energy peaks at different time scales that indicate the daily evolution of radon concentration. The composite seasonal plot shows that at least 21% of the average monthly radon concentration can be attributable to nonlocal effects. In a case study, it is observed that the time evolution of precipitation is one of the important governing factors of radon concentration near the surface. The activity of radon varies from 2 to 65 Bq/m3 with a mean of 12.35 Bq/m3 and ambient gamma dose levels varied between 141.8 and 244 nSv/h with a mean of 188.8 nSv/h.

Fourier transform power spectrum is a potential measure of tissue alignment in standard MRI: A multiple sclerosis study.

Loss of tissue coherency in brain white matter is found in many neurological diseases such as multiple sclerosis (MS). While several approaches have been proposed to evaluate white matter coherency including fractional anisotropy and fiber tracking in diffusion-weighted imaging, few are available for standard magnetic resonance imaging (MRI). Here we present an image post-processing method for this purpose based on Fourier transform (FT) power spectrum. T2-weighted images were collected from 19 patients (10 relapsing-remitting and 9 secondary progressive MS) and 19 age- and gender-matched controls. Image processing steps included: computation, normalization, and thresholding of FT power spectrum; determination of tissue alignment profile and dominant alignment direction; and calculation of alignment complexity using a new measure named angular entropy. To test the validity of this method, we used a highly organized brain white matter structure, corpus callosum. Six regions of interest were examined from the left, central and right aspects of both genu and splenium. We found that the dominant orientation of each ROI derived from our method was significantly correlated with the predicted directions based on anatomy. There was greater angular entropy in patients than controls, and a trend to be greater in secondary progressive MS patients. These findings suggest that it is possible to detect tissue alignment and anisotropy using traditional MRI, which are routinely acquired in clinical practice. Analysis of FT power spectrum may become a new approach for advancing the evaluation and management of patients with MS and similar disorders. Further confirmation is warranted.

Ultrafast coherent spectroscopic investigation on photosynthetic pigment chlorophyll a utilizing 20 fs pulses

Abstract Vibrational dynamics of the photosynthetic pigment chlorophyll a in solution have been investigated by degenerated three-pulse four-wave mixing spectroscopies (transient grating and photon echo) using 20 fs pulses. Real-time wave-packet motions of intramolecular vibrations were clearly observed in four-wave mixing signals. Twelve vibrational modes due to chlorophyll a in the region of energy ranging from 200 to 1400 cm−1 were found in the Fourier transform power spectra of coherent oscillations. We demonstrate that a specific light–matter interaction can be enhanced by a control of the temporal separation between the first and second pulses.

Periodic nanostructures self-formed on silicon and silicon carbide by femtosecond laser irradiation

Laser-induced periodic surface structures (LIPSS) were formed on Si and SiC surfaces by irradiations with femtosecond laser pulses in air. Different kinds of self-organized structures appeared on Si and SiC at laser fluences slightly higher than the damage threshold, which was measured by confocal laser scanning microscope. The characteristic spatial periodicity of every observed structure was estimated reading the peak values of the 2D Fourier transform power spectra obtained from SEM images. The evolution of the spatial periodicity was finally studied with respect to both the laser fluence and the number of laser pulses. As already observed for metals, the behavior of the spatial periodicity on laser fluence can be related to the parametric decay of laser light into surface plasma waves. Our results suggest a wide applicability of the parametric decay model on different materials, making the model a useful tool in view of different applications of LIPSS.

Extraction of the inherent nature of wind speed using wavelets and FFT

Due to technological advancement, availability of multi-megawatt wind turbines, ease of installation and maintenance, economic compatibility and commercial acceptance, wind power is being used globally for both grid-connected and off-grid applications. The wind power is intermittently available due to the fluctuating nature of the wind and hence needs to be understood well. Its variability was studied in this paper both in time and spatial domain. The present work utilized daily mean values of wind speed from different meteorological stations spread over the Kingdom of Saudi Arabia in conjunction with wavelet transform and fast Fourier transform power spectrum techniques to understand the dynamic nature of the wind at nine stations. The study found that wind speed changed by ±0.6 to ±1.6knots over a long period of about 10years depending on the locations. The long-term mean wind speed of 5.6, 8.9, 6.25, 8.1, 6.0, 7.1, 6.0, 8.6 and 7.3knots was obtained at Abha, Dhahran, Gizan, Guriat, Hail, Jeddah, Riyadh, Turaif and Yanbu, respectively.

Robust Features Of Surface Electromyography Signal

Nowadays, application of robotics in human life has been explored widely. Robotics exoskeleton system are one of drastically areas in recent robotic research that shows mimic impact in human life. These system have been developed significantly to be used for human power augmentation, robotics rehabilitation, human power assist, and haptic interaction in virtual reality. This paper focus on solving challenges in problem using neural signals and extracting human intent. Commonly, surface electromyography signal (sEMG) are used in order to control human intent for application exoskeleton robot. But the problem lies on difficulty of pattern recognition of the sEMG features due to high noises which are electrode and cable motion artifact, electrode noise, dermic noise, alternating current power line interface, and other noise came from electronic instrument. The main objective in this paper is to study the best features of electromyography in term of time domain (statistical analysis) and frequency domain (Fast Fourier Transform).The secondary objectives is to map the relationship between torque and best features of muscle unit activation potential (MaxPS and RMS) of biceps brachii. This project scope use primary data of 2 male sample subject which using same dominant hand (right handed), age between 20–27 years old, muscle diameter 32cm to 35cm and using single channel muscle (biceps brachii muscle). The experiment conduct 2 times repeated task of contraction and relaxation of biceps brachii when lifting different load from no load to 3kg with ascending 1kg The result shows that Fast Fourier Transform maximum power spectrum (MaxPS) has less error than mean value of reading compare to root mean square (RMS) value. Thus, Fast Fourier Transform maximum power spectrum (MaxPS) show the linear relationship against torque experience by elbow joint to lift different load. As the conclusion, the best features is MaxPS because it has the lowest error than other features and show the linear relationship with torque experience by elbow joint to lift different load.

Dealloying Multiphase AgCu Thin Films in Supercritical CO2

Multiphase AgCu thin films were dealloyed using a mixture of hexafluoroacetylacetone (hfacH) and H2O2 dissolved in supercritical CO2. AgCu alloys exhibit eutectic phase behavior, allowing the composition of the two phases to be fixed while varying the average size of the phase domains from 250 to 1000 nm by increasing the annealing temperature. Selective removal of Cu from both phases was observed, and higher concentrations of the etching solution increased the etching rate between 45 and 75 °C, where the reaction exhibited an apparent activation energy of ∼38 kJ/mol. The morphology after dealloying was quantified using the fast Fourier transform power spectrum obtained from electron microscopy images. For phase domains smaller than ∼500 nm, Ag atoms released in the open regions that had been occupied by the Cu-rich phase diffused separately or as clusters to the Ag-rich phase, forming a nanostructured morphology that mimicked the starting microstructure. For larger domains, stable Ag clusters (50 nm diameter) formed in the open regions, because the diffusion limit was reached, yielding an estimate of 4 × 10–12 cm2/s for the surface diffusivity in supercritical CO2.

The Study on Classification of High Resolution Remote Sensing Image in Saline Area based on Window Fourier Transform Power Spectrum Analysis

The image segmentation is the basis of object-based image analysis method,which is usually carried out based on the hypothesis of spectral homogeneity.But this hypothesis is not quite applied to the saline lake in arid region which composed of two surface features with high contrast(crystalline salt and brine) in spectrum.Aiming at the shortcoming of segmentation only based heterogeneity of spectrum and shape in object based image analysis methods,the segmentation algorithms based on texture are proposed.In this paper,we firstly extract texture features using window Fourier power spectrum method.Next,multi-resolution segmentation are carried out on texture image and multi-spectral image.Finally,we classify polygons produced by segmentation in multi-level.The paper takes SPOT 5 image acquired in November 2008 of Jilantai Saline Lake and the surrounding areas for example,and extracts saline lake from SPOT 5 image using the method mentioned above.The result shows that the proposed method is capable of effectively extracting features in saline area.

Lower-hybrid (LH) oscillitons evolved from ion-acoustic (IA)/ion-cyclotron (IC) solitary waves: effect of electron inertia

Abstract. Lower-hybrid (LH) oscillitons reveal one aspect of geocomplexities. They have been observed by rockets and satellites in various regions in geospace. They are extraordinary solitary waves the envelop of which has a relatively longer period, while the amplitude is modulated violently by embedded oscillations of much shorter periods. We employ a two-fluid (electron-ion) slab model in a Cartesian geometry to expose the excitation of LH oscillitons. Relying on a set of self-similar equations, we first produce, as a reference, the well-known three shapes (sinusoidal, sawtooth, and spiky or bipolar) of parallel-propagating ion-acoustic (IA) solitary structures in the absence of electron inertia, along with their Fast Fourier Transform (FFT) power spectra. The study is then expanded to illustrate distorted structures of the IA modes by taking into account all the three components of variables. In this case, the ion-cyclotron (IC) mode comes into play. Furthermore, the electron inertia is incorporated in the equations. It is found that the inertia modulates the coupled IA/IC envelops to produce LH oscillitons. The newly excited structures are characterized by a normal low-frequency IC solitary envelop embedded by high-frequency, small-amplitude LH oscillations which are superimposed upon by higher-frequency but smaller-amplitude IA ingredients. The oscillitons are shown to be sensitive to several input parameters (e.g., the Mach number, the electron-ion mass/temperature ratios, and the electron thermal speed). Interestingly, whenever a LH oscilliton is triggered, there occurs a density cavity the depth of which can reach up to 20% of the background density, along with density humps on both sides of the cavity. Unexpectedly, a mode at much lower frequencies is also found beyond the IC band. Future studies are finally highlighted. The appendices give a general dispersion relation and specific ones of linear modes relevant to all the nonlinear modes encountered in the text.