FFT Data Research Articles

An exploratory and comparative assessment of the tourist circulation at the level of some countries of the South-Eastern European union in the current pandemic context

The coronavirus epidemic (COVID19) has affected the global economy and the services sector. Quarantine measures related to travel restrictions have led to an unprecedented decline in the tourism industry with repercussions on tourism service providers, transport companies and state budgets. Travel is necessary for tourism, therefore, any factor that prevents travel can have a profound impact on the tourism industry. In the current pandemic context, the forecast in the field of tourist travel has played an important role in supporting the revival of this sector. In this study, econometric and interpretive methods were combined to predict the demand. In this study we approached a prediction model that is based on the seasonal stationary and adjustment of observed and FFT data. Experimental results show that the proposed prediction model has demonstrated a good medium-term forecast and can be used successfully in short and medium periods of time. For a certification of the exploratory evaluation of tourism forecasts there were comparatively analyzed the results obtained for three countries in south-eastern Central Europe, countries with similar natural and anthropic tourist resources (Bulgaria, Croatia and Romania).

XAI 알고리즘을 통한 전동기 고장 진단에서의 연속 웨이블릿 변환 데이터 성능 평가

The data mainly used for motor fault diagnosis is FFT. However, preprocessing such as continuous discrete wavelet transform is used. When using deep learning algorithms, the performance of the data is evaluated by the model output. However, in order to improve the learning possibilities and preprocessing performance of data, performance evaluation from a model perspective is required. For this purpose, data performance evaluation using the LRP algorithm, one of the XAI techniques, is studied. Initial fault state diagnosis using current data, which is difficult to solve with FFT data, is performed with STFT and CWT data, and performance is evaluated through LRP. Experimental Results STFT and CWT are preprocessing techniques that enable the use of current signals for early fault diagnosis. Among the two preprocessing methods, the use of CWT is more preferable because the flexibility of the preprocessing is increased.

Influence of Magnetic State Variation on Transformer Core Vibration Characteristics and Its Measurement

The variation of magnetic state of transformer often causes the violent vibration of the transformer various parts, especially the core. The most obvious magnetic state change of the transformer is usually caused by the DC component. In this paper, one kind of magnetic compensation method is adopted to suppress the DC bias, and the core vibration caused by the transformer magnetic state change is studied in detail. At first, on the basis of measuring the magnetostriction and calculating the vibration displacement of transformer core, the research on the vibration increment created by the DC bias is carried out. Secondly, the transformer core vibration before and after the DC bias suppression is simulated, and the difference of the transformer with a magnetic compensation capacity is analyzed. Finally, based on the VIBXPERT®II FFT data acquisition and signal analyzer, the vibration of measuring points under the different magnetic state and the different measuring point under the same magnetic state are collected. The vibration tendency of each measuring point is given with the variation of the magnetic state. Thus, the vulnerable spot of the core vibration and the basic law of the transformer vibration are obtained, which could provide a basic method for the reducing vibration.

Research on LFMCW Radar Velocity Ranging Optimization System Based on FPGA

Abstract Linear frequency modulation continuous wave (LFMCW) radar is widely used in the field of velocity measurement and ranging because of its high precision and good range resolution. The traditional LFMCW radar uses a single core FFT to do data processing, which is not very fast. This article utilize that advantages of fast and high degree of integration of FPGA, and propose a double-core FFT processor based on the use of the optimized CORDIC parallel algorithm to improve data processing speed, enhance real time, design and realize the calculation module of the double-core FFT data processing module and the distance measuring speed, and finishes the design of the LFMCW radar speed measuring and measuring system with real time and quick advantages. The experimental results show that the system has the characteristics of fast data processing and high reliability, and can measure the moving vehicle in real time and effectively.

Envelope dynamics and stability with non-linear space-charge forces

We developed a model to calculate the stability of Gaussian beam distributions with non-linear space-charge forces in the presence of random and skew-quadrupole errors. The effect of the space-charge force on the beam matrix is calculated analytically including full cross-plane coupling in 4D phase space, which allows us to perform fast parameter studies. For stability analysis, we find the fixed points of the beam including the space-charge forces and construct a Jacobi-matrix by slightly perturbing the periodic solution. The stability of envelope oscillations is inferred by eigenvalue analysis. Furthermore, we employ envelope tracking as a complementary method and compare the results of the eigenvalue analysis with FFT data from the tracked envelope. The non-linearity of the space-charge force in combination with lattice errors and beam coupling opens up for envelope-lattice resonances and envelope coupling resonances. Hitting these resonances leads to envelope blow-up, causing an effective beam mismatch. Therefore, we finally examine the effect of beam mismatch on the envelope tune-shift and its stability.

Parallel Memory Accessing for FFT Architectures

The current paper introduces an efficient technique for parallel data addressing in FFT architectures performing in-place computations. The novel addressing organization provides parallel load and store of the data involved in radix-r butterfly computations and leads to an efficient architecture when r is a power of 2. The addressing scheme is based on a permutation of the FFT data, which leads to the improvement of the address generating circuit and the butterfly processor control. Moreover, the proposed technique is suitable for mixed radix applications, especially for radixes that are powers of 2 and straightforward continuous flow implementation. The paper presents the technique and the resulting FFT architecture and shows the advantages of the architecture compared to hitherto published results. The implementations on a Xilinx FPGA Virtex-7 VC707 of the in-place radix-8 FFT architectures with input sizes 64 and 512 complex points validate the results.

A Comparative Study of FFT, DCT, and DWT for Efficient Arrhytmia Classification in RP-RF Framework

Computer-aided ECG classification is an important tool for timely diagnosis of abnormal heart conditions. This paper proposes a novel framework that combines the theory of compressive sensing with random forests to achieve reliable automatic cardiac arrhythmia detection. Furthermore, the paper evaluates the characterization power of FFT, DCT and DWT data transformations in order to extract significant features that will bring the additional boost to the classification performance. The experiments – carried out over MIT-BIH benchmark arrhythmia database, following the standards and recommended practices provided by AAMI – demonstrate that DWT based features exhibit better performances compared to other two feature extraction techniques for a relatively small number of random projected coefficients, i.e. after considerable (approx. 85%) dimensionality reduction of the input signal. The results are very promising, suggesting that the proposed model could be implemented for practical applications of real-time ECG monitoring, due to its low-complexity.

Pattern Identification on the Nonlinear Radial Motion of an Oscillating Spherical Bubble Using Neural Networks

The main goal of this article is to study the oscillatory motion of a spherical gas bubble immersed in a Newtonian liquid subjected to a harmonic pressure excitation. We use the classical Rayleigh-Plesset equation to study the radial motion of the bubble undergoing a forcing acoustic pressure field. The second order nonlinear ordinary differential equation that governs the bubble motion is solved through a robust fifth order Runge-Kutta scheme with adaptive time-step. Several interesting patterns are identified. First we develop an asymptotic solution for low amplitudes of excitation pressure to validate our numerical code. Then we develop a bifurcation diagram in order to show how the parameters of the flow modify the vibrational patterns of the bubble. We also train a neural network to identify the vibrational pattern through its FFT data. The combination of neural networks with a bifurcation diagram could be useful for the identification of the flow physical parameters in practical applications. For each pattern we also provide an analysis of the motion of the bubble on the phase-space and interpret physically the system behavior with its FFT. In addition, we analyze nonlinear patterns using standard tools of dynamical systems such as Poincaré sections and calculate the Lyapunov exponents of the system. Based on that, we have identified topological transitions in phase plane using for instance the analysis of Poincaré sections and the solution in the frequency spectrum. We have seen that the mechanisms that dominate the dynamics of the oscillating bubble is the competition of the acoustic field excitation with surface tension forces and momentum diffusion by the action of the surrounding fluid viscosity.

전기부하 패턴분류를 위한 신호처리 기법에 관한 연구

최근 사물인터넷 기반의 재해예방 기술이 개발되고 있다. 본 논문에서는 사물인터넷기반의 공동주택용 자율전기안전관리 기술 개발을 위하여 부하 전류 파형을 FFT와 MFCC를 이용하여 신호변환 후 신경회로망 모델에 적용하여 정확도가 개선된 전기 부하 패턴분류 시스템을 제안한다. 오실로스코프와 CT를 이용하여 측정한 전기 부하의 전류 파형을 FFT 알고리즘을 적용한 후 신경회로망을 이용하여 단일부하패턴 분류 실험을 하였다. 본 연구를 통하여 부하의 특성을 파악함으로서 고장에 대해 보다 신속하고 정확하게 대처할 수 있을 것으로 예측된다. Recently several techniques for disaster prevention based on IoT(Internet of Things) are being developed. In this paper, a new smart pattern classification method for electric loads is proposed. CT(Current Transformer) data are extracted from electric loads, and then the sampled CT data are converted using FFT and MFCC. FFT and FMCC data are used for the input data of neural networks. Experiments were conducted using FFT and MFCC data for 7 kinds of electric loads. Experiments results indicate the superiority of MFCC in comparison to FFT.

Low-Power Split-Radix FFT Processors Using Radix-2 Butterfly Units

Split-radix fast Fourier transform (SRFFT) is an ideal candidate for the implementation of a low-power FFT processor, because it has the lowest number of arithmetic operations among all the FFT algorithms. In the design of such processors, an efficient addressing scheme for FFT data as well as twiddle factors is required. The signal flow graph of SRFFT is the same as radix-2 FFT, and therefore, the conventional address generation schemes of FFT data could also be applied to SRFFT. However, SRFFT has irregular locations of twiddle factors and forbids the application of radix-2 address generation methods. This brief presents a shared-memory low-power SRFFT processor architecture. We show that SRFFT can be computed by using a modified radix-2 butterfly unit. The butterfly unit exploits the multiplier-gating technique to save dynamic power at the expense of using more hardware resources. In addition, two novel address generation algorithms for both the trivial and nontrivial twiddle factors are developed. Simulation results show that compared with the conventional radix-2 shared-memory implementations, the proposed design achieves over 20% lower power consumption when computing a 1024-point complex-valued transform.

Symmetric small-aperture arrays for three-dimensional bearing estimation

Small aperture arrays (size less than a wavelength) can be used for passive direction of arrival (DOA) estimation of both broadband and narrowband signals in the frequency domain. Phase differences across the array are measured in the frequency domain and can be spectrally averaged for stationary DOA and frequencies if desired. Data windowing will bias the DOA measurement toward the center of the FFT data buffer and is useful to prevent spectral leakage from strong target signals overshadowing weak target signals. The array is capable of measuring multiple target DOAs so long as each target produces unique frequencies. Broadband signals from targets can be collected from the FFT bins and grouped by arrival angle using a bearing histogram. The Cramer-Rao lower bound (CRLB) for bearing accuracy is presented as a function of frequency, aperture, and signal-to-noise ratio (SNR). The reduction in DOA accuracy due to a small aperture can be overcome if the SNR is sufficiently high. Using symmetry in 2D and 3D array geometries, we show how the azimuth and elevation angles can be separately measured. Examples are given for several single and multiple targets and different array shapes.

Advanced signal processing techniques and optimized measurements to extract wind turbine signatures in nearby homes

Previous measurements in homes near wind turbines indicate higher pressure levels below 10 Hz than audible pressure levels measured at the same time and location (ASA, vol. 20, 2013 Dooley & Metelka). Blade pass harmonic pressures were proven to be higher relative to basement ground-borne vibration and seismic vibration in floors throughout the home are reexamined simultaneous to broadband pressure. Although the pressure vs. frequency distribution appear to be the same at different locations in one room, they differ when compared to other rooms due to room dimensions. Further multichannel signal processing using a variety of different sensors at various locations inside a home identify areas in a home that are least affected by wind turbine low frequency discrete harmonics as well as acoustic metrics. Wind direction, wind speed, and other factors are precisely measured simultaneously. Sound level metrics inside homes are also compared to narrowband FFT data in an attempt to quantify annoyance and derive alternate metrics.

Coarse Symbol Timing Synchronization Improved Algorithm for CMMB Mobile TV

There are some multipath and frequency offset in wireless transmission environment, in order to determine the correct starting position of each OFDM symbol, CMMB system must achieve accurate symbol synchronization for send- ing and receiving data, making FFT data transform window position in receiver consistent with IFFT window position in sender. This paper combined the specific frame structure of CMMB standard protocol, analyzed some influences of sym- bol synchronization timing errors in system, discussed the traditional ML (Maximum Likelihood) algorithm, the non data aided algorithm and the reverse conjugate symmetry direct algorithm, and based on the characteristics of these algorithm, proposed a coarse symbol timing synchronization improved algorithm according to CMMB mobile TV, the feasibility of this algorithm is verified in AWGN and multipath channel. Simulation results show that the performance of improved al- gorithm is better, there is no multi-peak of ML algorithm, and don't worry about appearing lat roof phenomenon like no data aided algorithm, and it also eliminates adjacent peak interference of the reverse conjugate symmetry direct algorithm, this algorithm is not limited by SNR, even in bad multipath channel condition, the approximate starting position of sym- bol can be estimated.

FLUID-STRUCTURE INTERACTION IN A U-TUBE WITH SURFACE ROUGHNESS AND PRESSURE DROP

In this research, the surface roughness affecting the pressure drop in a pipe used as the steam generator of a PWR was studied. Based on the CFD (Computational Fluid Dynamics) technique using a commercial code named ANSYS-FLUENT, a straight pipe was modeled to obtain the Darcy frictional coefficient, changed with a range of various surface roughness ratios as well as Reynolds numbers. The result is validated by the comparison with a Moody chart to set the appropriate size of grids at the wall for the correct consideration of surface roughness. The pressure drop in a full-scale U-shaped pipe is measured with the same code, correlated with the surface roughness ratio. In the next stage, we studied a reduced scale model of a U-shaped heat pipe with experiment and analysis of the investigation into fluid-structure interaction (FSI). The material of the pipe was cut from the real heat pipe of a material named Inconel 690 alloy, now used in steam generators. The accelerations at the fixed stations on the outer surface of the pipe model are measured in the series of time history, and Fourier transformed to the frequency domain. The natural frequency of three leading modes were traced from the FFT data, and compared with the result of a numerical analysis for unsteady, incompressible flow. The corresponding mode shapes and maximum displacement are obtained numerically from the FSI simulation with the coupling of the commercial codes, ANSYS-FLUENT and TRANSIENT_STRUCTURAL. The primary frequencies for the model system consist of three parts: structural vibration, BPF(blade pass frequency) of pump, and fluid-structure interaction.

Morphology tuning of mono-disperse silver nanoparticles by reaction temperature adjustment

Mono-disperse silver nanoparticles with tunable morphologies have been fabricated by reducing AgNO3 in the presence of N-dimethylformamide (DMF) and larger molecular weight poly (vinylpyrrolidone) (PVP). By adjusting the reaction temperature, the conversion of the morphology can be easily and effectively controlled. The crystal structures and growth mechanism of mono-disperse silver nanoparticles were studied by using TEM, HR-TEM, FFT, XRD and UV-Vis spectra data. The results show that the morphologies of nanoparticles with spherical shape can be adjusted to a truncated triangle/hexagon along with the change of reaction temperature from 80 to 120 °C. It is found that the shape transformation from sphere to truncated triangle is caused by the difference in surface energy and the selective adsorption of PVP on silver atom.

Research on Interpolation Algorithm for DSSS Signal Receiver

For Direct Sequence Spread Spectrum (DSSS) receiver, a parallel acquisition algorithm based on FFT-IFFT is proposed to improve speed of the DSSS signal acquisition. In order to ensure the FFT data points is equal to a power of 2(2N), Interpolation Algorithm is always used. In this paper, three interpolation algorithms are introduced in detail, and they are analyzed theoretically and compared by quantitative simulation, the resources occupied and test performance verification. We draw the conclusion that the linear interpolation is the optimal algorithm which offers the effective technique for the implementation of DSSS signal receiver.

Electrospun nanofibers as a tool for architecture control in engineered cardiac tissue

This paper presents an in vitro system for cardiac tissue engineering based on cardiomyocytes cultured on electrospun polymethylglutarimide (PMGI) nanofibrous meshes either imprinted on solid substrate or suspended in space. Special care was taken over the ability to control the tissue architecture. The electrospinning process allowed nano-scale diameter PMGI fibers with different positioning density to be collected in a random or in an aligned way that defines the general configuration of the mesh. Micro-imprinted on solid substrate nanofibers guarantee aligned cell growth, when the distance between them is 30 μm or less. Suspended in 3D space, nanofibers define the overall architecture of the tissue, depending on orientation and positioning density of the nanofibers. As a result, cardiac cells proliferated into contractile tissue filaments, open-worked tissue meshes and continuous anisotropic cell sheets. Alignment of the cells was characterized by elongation of the cell shape and orientation of the α-actin filaments supported by the FFT data. The advantage of this method is its ability to maintain both three-dimensionality and structural anisotropy.

Development of a Two-Dimensional Force Model and Data Analysis for the Tire Uniformity Testing Machine

Force model of tire uniformity testing system and data analysis method are fundamental to a tire uniformity testing machine. Based on theoretical analysis, this paper proposes a two-dimensional force model to calculate tire’s radial and lateral force, confirm the mechanical structures of the existing tire uniformity testing machine’s testing system and verify the validity of its testing method by the model. According to this two-dimensional force model and FFT data analysis method, the YLJ series tire uniformity testing machine is developed. It is mainly applied for fully auto online uniformity test and size deviation. The authors also explained the operational principle, data measurement and analysis procedure of the YLJ series tire uniformity testing machine.

633 床マットセンサーによる寝位の身体挙動について(感性と人体特性,OS-7 ヒューマンダイナミクス,総合テーマ「伝統を,未来へ!」)

It is said that 20% people of population have several troubles of sleeping in Japan. In this study, we aimed for the development to collect the human condition including heartbeat count, breathing count and turn over in bed by use of bed mat sensor. In this study, polymer sheet sensors distributed in matrix shape are used. A basic examination was performed in this study to obtain heartbeat count and breathing count by use of small pressure sensors. We compared FFT data of normal pulse date and pulse date including wave from arrhythmia and FFT data of breath. We will improve ubiquitous degree of the sensor mat in future, it reports.

Identification of hip fracture patients from radiographs using Fourier analysis of the trabecular structure: a cross-sectional study

BackgroundThis study presents an analysis of trabecular bone structure in standard radiographs using Fourier transforms and principal components analysis (PCA) to identify contributions to hip fracture risk.MethodsRadiographs were obtained from 26 hip fracture patients and 24 controls. They were digitised and five regions of interest (ROI) were identified from the femoral head and neck for analysis. The power spectrum was obtained from the Fourier transform of each region and three profiles were produced; a circular profile and profiles parallel and perpendicular to the preferred orientation of the trabeculae. PCA was used to generate a score from each profile, which we hypothesised could be used to discriminate between the fracture and control groups. The fractal dimension was also calculated for comparison. The area under the receiver operating characteristic curve (Az) discriminating the hip fracture cases from controls was calculated for each analysis.ResultsTexture analysis of standard radiographs using the fast Fourier transform yielded variables that were significantly associated with fracture and not significantly correlated with age, body mass index or femoral neck bone mineral density. The anisotropy of the trabecular structure was important; both the perpendicular and circular profiles were significantly better than the parallel-profile (P < 0.05). No significant differences resulted from using the various ROI within the proximal femur. For the best three groupings of profile (circular, parallel or perpendicular), method (PCA or fractal) and ROI (Az = 0.84 – 0.93), there were no significant correlations with femoral neck bone mineral density, age, or body mass index. PCA analysis was found to perform better than fractal analysis (P = 0.019).ConclusionsBoth PCA and fractal analysis of the FFT data could discriminate successfully between the fracture and control groups, although PCA was significantly stronger than fractal dimension. This method appears to provide a powerful tool for the assessment of bone structure in vivo with advantages over standard fractal methods.