Fast Fourier Transform Approach Research Articles

Pengaruh Variasi Parameter Filter Terhadap Harmonisa Pada Operasi PLTS Terintegrasi Sistem Tenaga Listrik

This paper provides a comprehensive harmonic picture of Photovoltaic operations integrated with the Electric Power System (Photovoltaic on-grid). Harmonics in Photovoltaic on-grid are generated from the inverter. One way to reduce harmonics is by installing a filter. Apart from reducing harmonics, filters can improve the system power factor value. This research examines the effect of variations in Photovoltaic on-grid filter parameters on inverter power capacity using Simulink/Matlab simulation. The FFT (Fast Fourier Transform) method is used to determine the harmonic order and THD of the current and voltage of the system on the side before and after the filter. The simulation results show changes in filter parameter variations for Qc (Var) values ​​giving THDi and THDv values ​​before and after filter installation using the FFT approach.

FFT-Based Approach for the Mechanical Analysis of Superconducting Rutherford-Type Cables

Low-temperature superconductors are widely used in high field accelerator magnets, mostly within Rutherford type cables. We have proposed the “CoCaSCOPE” approach in order to build a numerical model of impregnated low-temperature Nb <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> Sn superconducting Rutherford-type cables dedicated to mechanical computation. Here the strand structure is described as a bi-metallic material: a copper core, a superconducting bundle region and an outer copper ring. In this paper, we explore the use of the distributed solver AMITEX_FFTP based on Fast Fourier Transform (FFT). The main interest of this method is to reduce the simulation time. This approach is investigated for structures with linear material behavior in this paper. This work compares the results from the FFT approach (using AMITEX) and from the 3D Finite Elements approach (using Cast3M). In this way, we can demonstrate the higher performances of FFT-based solving method compared to the finite elements method for multi-scale structure such as Rutherford-type cables in terms of computation time. With this approach, we can reduce the computation time or, alternatively, increase the size of our models in order to analyze the behavior of a macroscale model under mechanical solicitation.

Training FFT to Select Beams in Massive MIMO

In this letter, we propose new trainable Fast Fourier Transform (FFT) structures to increase the accuracy of beamspace transformation in the multi-user (MU) mode of Massive Multiple Input Multiple Output (MIMO) receiver. The FFT is a widely employed beamspace transformation technique, thanks to its low transforming complexity. Unfortunately, there is a significant performance loss of MU signal detection in the FFT beamspace, as default FFT beams are not co-directed with angles of arrivals. We address this issue with trainable FFT that outperforms not only fixed FFT approaches, but also other trainable FFT techniques.

Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach

Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid.

Early Pharmacological Profiling of Antiproliferative Compounds by Live Cell Imaging.

Natural products represent an excellent source of unprecedented anticancer compounds. However, the identification of the mechanism of action remains a major challenge. Several techniques and methodologies have been considered, but with limited success. In this work, we explored the combination of live cell imaging and machine learning techniques as a promising tool to depict in a fast and affordable test the mode of action of natural compounds with antiproliferative activity. To develop the model, we selected the non-small cell lung cancer cell line SW1573, which was exposed to the known antimitotic drugs paclitaxel, colchicine and vinblastine. The novelty of our methodology focuses on two main features with the highest relevance, (a) meaningful phenotypic metrics, and (b) fast Fourier transform (FFT) of the time series of the phenotypic parameters into their corresponding amplitudes and phases. The resulting algorithm was able to cluster the microtubule disruptors, and meanwhile showed a negative correlation between paclitaxel and the other treatments. The FFT approach was able to group the samples as efficiently as checking by eye. This methodology could easily scale to group a large amount of data without visual supervision.

Fully Dynamic Earthquake Cycle Simulations on a Nonplanar Fault Using the Spectral Boundary Integral Element Method (sBIEM)

ABSTRACT One of the most suitable methods for modeling fully dynamic earthquake cycle simulations is the spectral boundary integral element method (sBIEM), which takes advantage of the fast Fourier transform (FFT) to make a complex numerical dynamic rupture tractable. However, this method has the serious drawback of requiring a flat fault geometry due to the FFT approach. Here, we present an analytical formulation that extends the sBIEM to a mildly nonplanar fault. We start from a regularized boundary element method and apply a small-slope approximation of the fault geometry. Making this assumption, it is possible to show that the main effect of nonplanar fault geometry is to change the normal traction along the fault, which is controlled by the local curvature along the fault. We then convert this space–time boundary integral equation of the normal traction into a spectral-time formulation and incorporate this change in normal traction into the existing sBIEM methodology. This approach allows us to model fully dynamic seismic cycle simulations on nonplanar faults in a particularly efficient way. We then test this method against a regular BIEM for both rough-fault and seamount-fault geometries and demonstrate that this sBIEM maintains the scaling between the fault geometry and slip distribution.

A high-resolution gravimetric geoid model for Kingdom of Saudi Arabia

A high-resolution gravimetric geoid model for the Kingdom of Saudi Arabia area was determined. A data set of 459,848 land gravity, 80,632 shipborne marine gravity data, DTU17 altimetry gravity model, and XGM2019e global geopotential model. The computation strategy followed for modelling of the gravimetric geoid is based on the Remove-Compute-Restore with Residual Terrain Model reduction and the 1D- Fast Fourier Transform approach technique. The geoid heights have been determined by using the Stokes integral with Wong–Gore modification. The accuracy of the resulting geoid models was evaluated by comparing them with 5385 GPS/levelling points. The geoid accuracy over all the kingdom is better than 11 cm in STD sense and the comparison in sub-areas obtained accuracy range from 2.8 to 11.9 cm according to the density of gravity observations.

Comparison between traditional fast Fourier transform and marginal spectra using the Hilbert–Huang transform method for the broadband spectral analysis of the electroencephalogram in healthy humans

AbstractThe fast Fourier transform (FFT) has been the main tool for electroencephalographic (EEG) Spectral Analysis (SPA). However, as the EEG dynamics show nonlinear and non‐stationary behavior, results using the FFT approach may result meaningless. A novel method has been developed for the analysis of nonlinear and non‐stationary signals known as the Hilbert–Huang transform method. In this study we analyze the differences for the broadband (SPA) of the EEG using the traditional FFT approach with those calculated with the Hilbert Marginal Spectra (HMS) after decomposition of the EEG with a multivariate empirical mode decomposition algorithm. EEG segments recorded from 19 leads of 47 healthy volunteers were studied. Statistically significant differences between methods were found for almost all leads by variance analyses. The agreement assessment shows that mean weighted frequencies have a good agreement for almost all bands, with the exception of beta‐2 and gamma bands where values for the HMS where higher than 3 Hz. Also the HMS method received lower than 5% energy values for alpha activity with an increment in the adjacent bands. The HMS may be considered a good alternative for the SPA of the EEG when nonlinearity or non‐stationarity may be present.

Quantifying upper limb tremor in people with multiple sclerosis using Fast Fourier Transform based analysis of wrist accelerometer signals.

IntroductionTremor is a disabling symptom of Multiple Sclerosis (MS). The development of objective methods of tremor characterisation to assess intervention efficacy and disease progression is therefore important. The possibility of using a Fast Fourier Transform (FFT) method for tremor detection was explored.MethodsAcceleration from a wrist-worn device was analysed using FFTs to identify and characterise tremor magnitude and frequency. Processing parameters were explored to provide insight into the optimal algorithm. Participants wore a wrist tri-axial accelerometer during 9 tasks. The FAHN clinical assessment of tremor was used as the reference standard.ResultsFive people with MS and tremor (57.6 ± 15.3 years, 3 F/2M) and ten disease-free controls (42.4 ± 10.9 years, 5 M/5F) took part. Using specific algorithm settings tremor identification was possible (peak frequency 3–15Hz; magnitude greater than 0.06 g; 2 s windows with 50% overlap; using 2 of 3 axes of acceleration), giving sensitivity 0.974 and specificity 0.971 (38 tremor occurrences out of 108 tasks, 1 false positive, 2 false negatives). Tremor had frequency 3.5–13.0 Hz and amplitude 0.07–2.60g.ConclusionsUpper limb tremor in people with MS can be detected using a FFT approach based on acceleration recorded at the wrist, demonstrating the possibility of using this minimally encumbering technique within clinical practice.

Structural flexibility identification and fast-Bayesian-based uncertainty quantification of a cable-stayed bridge

Most current uncertainty analyses are limited to the basic modal parameters such as frequencies and mode shapes, which are not enough to evaluate structural performance. In order to quantify the uncertainty of the deep parameters, a quantitative technique combining the mass-changing strategy and the fast Bayesian fast Fourier transform (FFT) approach is proposed. Basic modal parameters and their variance and coefficient of variation (c.o.v) are obtained from the fast Bayesian FFT approach, which only uses the ambient testing data. Deep parameters (scaling factor and flexibility matrix) are calculated on the mass-changing strategy. On this basis, the uncertainty quantification of deep parameters is strictly derived by the first-order expansion and used to predict the confidence interval of deflection. In this study, a static load testing of the Sutong Bridge is utilized to verify the effectiveness and reliability of the proposed uncertainty quantification technique. The structural flexibility matrix and its confidence interval are identified and then applied to predict the deflection of the main span under truck loads. The predicted results agree well with the displacement measurements, which are also within the estimated confidence interval.

Quantifying deformations and strains in human intervertebral discs using Digital Volume Correlation combined with MRI (DVC-MRI)

Physical disruptions to intervertebral discs (IVDs) can cause mechanical changes that lead to degeneration and to low back pain which affects 75% of us in our lifetimes. Quantifying the effects of these changes on internal IVD strains may lead to better preventative strategies and treatments. Digital Volume Correlation (DVC) is a non-invasive technique that divides volumetric images into subsets, and measures strains by tracking the internal patterns within them under load. Applying DVC to MRIs may allow non-invasive strain measurements. However, DVC-MRI for strain measurements in IVDs has not been used previously. The purpose of this study was to quantify the strain and deformation errors associated with DVC-MRI for measurements in human IVDs.Eight human lumbar IVDs were MRI scanned (9.4 T) for a ‘zero-strain study’ (multiple unloaded scans to quantify noise within the system), and a loaded study (2 mm axial compression). Three DVC methodologies: Fast-Fourier transform (FFT), direct correlation (DC), and a combination of both FFT and DC approaches were compared with subset sizes ranging from 8 to 88 voxels to establish the optimal DVC methodology and settings which were then used in the loaded study.FFT + DC was the optimal method and a subset size of 56 voxels (2520 µm) was found to be a good compromise between errors and spatial resolution. Displacement and strain errors did not exceed 28 µm and 3000 microstrain, respectively.These findings demonstrate that DVC-MRI can quantify internal strains within IVDs non-invasively and accurately. The method has unique potential for assessing IVD strains within patients.

Fast Radix-32 Approximate DFTs for 1024-Beam Digital RF Beamforming

The discrete Fourier transform (DFT) is widely employed for multi-beam digital beamforming. The DFT can be efficiently implemented through the use of fast Fourier transform (FFT) algorithms, thus reducing chip area, power consumption, processing time, and consumption of other hardware resources. This paper proposes three new hybrid DFT 1024-point DFT approximations and their respective fast algorithms. These approximate DFT (ADFT) algorithms have significantly reduced circuit complexity and power consumption compared to traditional FFT approaches while trading off a subtle loss in computational precision which is acceptable for digital beamforming applications in RF antenna implementations. ADFT algorithms have not been introduced for beamforming beyond $N = 32$, but this paper anticipates the need for massively large adaptive arrays for future 5G and 6G systems. Digital CMOS circuit designs for the ADFTs show the resulting improvements in both circuit complexity and power consumption metrics. Simulation results show similar or lower critical path delay with up to 48.5% lower chip area compared to a standard Cooley-Tukey FFT. The time-area and dynamic power metrics are reduced up to 66.0%. The 1024-point ADFT beamformers produce signal-to-noise ratio (SNR) gains between 29.2--30.1 dB, which is a loss of $\le$ 0.9 dB SNR gain compared to exact 1024-point DFT beamformers (worst case) realizable at using an FFT.

A two-stage Bayesian algorithm for finite element model updating by using ambient response data from multiple measurement setups

This study presents a two-stage Bayesian finite element model updating procedure by using acceleration response measurements obtained from multiple setups. In the presented methodology, parametric uncertainties for the modal parameters are estimated by using the Bayesian Fast Fourier Transform Approach (BFFTA). Different from the previous Bayesian methods, a block diagonal covariance matrix is modeled for prior estimation of measured modal parameters. In addition, the modelling error in the eigenvalue equations is considered as soft constraints to be updated. Numerical and experimental studies are presented to validate the proposed method. The effect of soft constraints on the identification results as well as their posterior uncertainties are investigated. According to the results, it is shown that the proposed methodology can identify the most probable finite element model parameters with high level of accuracy. In addition, the posterior uncertainties obtained by the proposed procedure are significantly small when compared to the methods that consider rigid constraints for prediction and/or modelling error.

A mode shape assembly algorithm by using two stage Bayesian Fast Fourier Transform Approach

Abstract Operational modal analysis may require identifying global modal shapes by using multiple setup measurements. For this purpose, various algorithms have been developed which make use of the Bayesian approach to estimate the global mode shapes. The main motivation of the available Bayesian approaches is based on the estimation of the optimal global mode shape vector directly from Fast Fourier Transform data or assembling the local mode shapes that are identified in the individual setups by using Gaussian approximation. In this study, the two-stage Bayesian Fast Fourier Transform Approach which is originally applied to single setups is implemented to multiple setup problems for well separated modes. Analytically it is shown that the resulting formulation is the same for the mode shape assembly by using the Gaussian approximation. In addition, the weights of individual setups in the global mode shape vector is analytically calculated which depend on the Hessian matrix for local mode shapes. To validate the proposed methodology, a numerical example that considers setup-to-setup variability of modal signal-noise ratios is presented. For comparison purposes a ten-story shear frame model is experimentally investigated, and the measurements of a benchmark bridge structure are considered in the verification of the current procedure.

A high-resolution gravimetric quasigeoid model for Vietnam

A high-resolution gravimetric quasigeoid model for Vietnam and its surrounding areas was determined based on new gravity data. A set of 29,121 land gravity measurements was used in combination with fill-in data where no gravity data existed. Global Gravity field Models plus Residual Terrain Model effects and gravity field derived from altimetry satellites were used to provide the fill-in information over land and marine areas. A mixed model up to degree/order 719 was used for the removal of the long and medium wavelengths and the calculation of the quasigeoid restore effects. The residual height anomalies have been determined employing the Stokes integral using the Fast Fourier Transform approach and deterministic kernel modification proposed by Wong–Gore, as well as by means of Least-Squares Collocation. The accuracy of the resulting quasigeoid models was evaluated by comparing with height anomalies derived from 812 co-located GNSS/levelling points. Results are very similar; both local quasigeoid models have a standard deviation of 9.7 cm and 50 cm in mean bias when compared to the GNSS/levelling points. This new local quasigeoid model for Vietnam represents a significant improvement over the global models EIGEN-6C4 and EGM2008, which have standard deviations of 19.2 and 29.1 cm, respectively, for this region.

Multibeam Digital Array Receiver Using a 16-Point Multiplierless DFT Approximation

An N-element array with receivers subject to an N-point spatial fast Fourier transform (FFT) leads to N directionally orthogonal radio frequency (RF) beams. FFTs are fast algorithms for computing the N-point discrete Fourier transform (DFT) at reduced complexity. The brute-force computation of a DFT requires O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) multiplications while an FFT provides the same computation at O(N log N) multiplications. The digital chip area and power consumption of the DFT computation are still dominated by the multipliers required by the FFT used. In this paper, an approximation to the 16-point DFT is proposed which maintains mathematical properties close to the ideal 16-point DFT to obtain 16 RF beams by computing an approximate spatial DFT in every clock cycle at significantly lower area and power in the digital realization. The proposed approximation can be implemented using FFT-like fast algorithms that are multiplierless, thereby further reducing the digital chip area and power consumption associated with multiplication in a conventional FFT approach to zero. A 16-beam beamformer employing a 16-element linear array of patch antennas, direct-conversion receivers, and a Xilinx Virtex6 field-programmable gate array-based real-time digital back-end clocked at 240 MHz are described as an example realization of 16 complex-valued (IQ) receive-mode RF beams, centered at 2.4 GHz with 120 MHz of bandwidth per beam.

Calculate tail quantiles of compound distributions

We evaluate the performance of different approaches for estimating quantiles of compound distributions, which are widely used for risk quantification in the banking and insurance industries. We focus on three approaches: (1) single-loss approximation (SLA), (2) perturbative expansion correction (PEC) and (3) the fast Fourier transform (FFT). We demonstrate that both the SLA and PEC approaches are accurate only for tail quantiles of subexponential distributions. The PEC approach produces accurate estimates for quantiles greater than 95, while the SLA can only do this for quantiles greater than 99.9. Thus, the PEC approach dominates the SLA approach. The FFT approach consistently gives the most accurate estimates for every distribution. However, the FFT approach is substantially less time efficient than the PEC or SLA approaches, which are closed-form solutions. We contribute to the literature by providing practical guidance on selecting appropriate approaches for the various parametric distributions and quantiles used in the banking and insurance industries.

Intra-vineyard variability description through satellite-derived spectral indices as related to soil and vine water status

A time series of Landsat 8 OLI multispectral images acquired in the period May 2013 - February 2016 was used to investigate vineyard behaviour in terms of vigour and water content. The study site was located in the Castel del Monte DOCG area; a 'Moscato Reale' (syn. 'Moscato Bianco') vineyard was analysed. Normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were calculated for all images (preventively calibrated and atmospherically corrected) to describe, at pixel level (30×30 m), vigour, plant and soil water status. Spectral indices cyclicity was also assessed to explore dynamics of vines growing season. Satellite-derived information was compared with ground parameters (midday stem water potential and soil water content), correlation tested and regression models for parameter estimation calibrated. Periodicity of vigour (NDVI) and water content (NDWI') along time was described using a Fast Fourier Transform approach, finding that the most vigorous part of vineyard corresponded to the most regular (cyclic) ones. Middle resolution multispectral imagery from satellite can be effectively used, at vineyard level, to describe cyclicity, water status and soil moisture. This is an important issue to focus on since, as Landsat OLI dataset is free, the entire process is economic enough to be consistent with cost and income of the farming system.

Automated Scalable Address Generation Patterns for 2-Dimensional Folding Schemes in Radix-2 FFT Implementations

Hardware-based implementations of the Fast Fourier Transform (FFT) are highly regarded as they provide improved performance characteristics with respect to software-based sequential solutions. Due to the high number of operations involved in calculations, most hardware-based FFT approaches completely or partially fold their structure to achieve an efficient use of resources. A folding operation requires a permutation block, which is typically implemented using either permutation logic or address generation. Addressing schemes offer resource-efficient advantages when compared to permutation logic. We propose a systematic and scalable procedure for generating permutation-based address patterns for any power-of-2 transform size algorithm and any folding factor in FFT cores. To support this procedure, we develop a mathematical formulation based on Kronecker products algebra for address sequence generation and data flow pattern in FFT core computations, a well-defined procedure for scaling address generation schemes, and an improved approach in the overall automated generation of FFT cores. We have also performed an analysis and comparison of the proposed hardware design performance with respect to a similar strategy reported in the recent literature in terms of clock latency, performance, and hardware resources. Evaluations were carried on a Xilinx Virtex-7 FPGA (Field Programmable Gate Array) used as implementation target.

Grouping FFT Based Two-Stage High Sensitivity Signal Acquisition With Sign Transitions

The acquisition performance of weak global navigation satellite system signals, especially those with secondary codes, is susceptible to sign transitions. To better understand and overcome the negative impact of sign transitions, this paper derived a new receiver auto-correlation function. The straightforward formula shows that sign transitions can reduce the accuracy of the Doppler estimate. To meet the initialization requirements of the tracking block, a two-stage high-sensitivity acquisition frame is proposed based on sign combinations search using matrix notation. The first stage adopts the conventional non-coherent combination (NC) algorithm to obtain the coarse code phase. And the second stage achieves high-resolution frequency estimation through fast Fourier transform (FFT). Besides, a novel grouping FFT algorithm is proposed to reduce the complexity of the second stage. The Beidou navigation satellite system (BDS) B1I signal is used as an example to verify the performances. Compared with conventional NC algorithm, the statistical performance of the new algorithm, in terms of the detection probabilities and frequency errors, can be greatly improved. To be specific, the proposed algorithm can actualize the 90% detection possibility of BDS B1I signal at a carrier-to-noise ratio (C/N0) of 23.9 dB-Hz within 200 ms with a Doppler accuracy of about 31 Hz. And the computing load of the second stage is reduced by about 11.6% compared with the conventional FFT approach. Actual data test further verifies the superiority of the new method. Inevitably, the total processing time increases by about 30%.