IMPROVED FOURIER ALGORITHM FOR CORRECTING POWER SYSTEM FREQUENCY DEVIATION

On the basis of high precision requirement for input signals in the power system protection and control system,this paper,only for the influence of power system frequency deviation on extracting fundamental harmonic,studies the amplitude error of Fourier algorithm,presents a method of correcting frequency deviation,and further derives the formulas of improved Fourier algorithm.The simulation results verified the effectiveness of the algorithm,it not only can greatly weaken the influence of frequency deviation,but also increase the precision of the power system protection and control.As a result the study in this paper has practical application value.

Fast Fourier single-pixel imaging based on Sierra–Lite dithering algorithm

The single-pixel imaging(SPI) technique is able to capture two-dimensional(2 D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging(FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns(also known as grayscale sinusoidal patterns)cannot be well displayed on the digital micromirror device(DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra–Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.

Anti-aliasing nonstationary signals detecion algorithm based on interpolation in the frequency domain using the short time Fourier transform

To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.

Adaptive split-step Fourier method for simulating ultrashort laser pulse propagation in photonic crystal fibres

In this paper, the generalized nonlinear Schrodinger equation （GNLSE） is solved by an adaptive split-step Fourier method （ASSFM）. It is found that ASSFM must be used to solve GNLSE to ensure precision when the soliton selffrequency shift is remarkable and the photonic crystal fibre （PCF） parameters vary with the frequency considerably. The precision of numerical simulation by using ASSFM is higher than that by using split-step Fourier method in the process of laser pulse propagation in PCFs due to the fact that the variation of fibre parameters with the peak frequency in the pulse spectrum can be taken into account fully.

Fourier hologram method using Gerchberg-Saxton algorithm for parallel femtosecond laser processing

In order to improve femtosecond laser throughput,a parallel processing system consisting of liquid crystal on silicon(LCOS)device as spatial light modulator is put forward.A method is described for displaying Fourier hologram on LCOS,and a high uniformity of several diffraction peaks in the computer reconstruction is achieved.Application of this method to the parallel femtosecond laser processing is also demonstrated,and two intersecting rings and three tangent rings are fabricated respectively by one time in the photoresist.

A Biproportional Construction Algorithm for Correctly Calculating Fourier Series of Aperiodic Non-Sinusoidal Signal

The Fourier series (FS) applies to a periodic non-sinusoidal function satisfying the Dirichlet conditions, whereas the being-processed function in practical applications is usually an aperiodic non-sinusoidal signal. When is aperiodic, its calculated FS is not correct, which is still a challenging problem. To overcome the problem, we derive a direct calculation algorithm, a constant iteration algorithm, and an optimal iteration algorithm. The direct calculation algorithm correctly calculates its Fourier coefficients (FCs) when is periodic and satisfies the Dirichlet conditions. Both the constant iteration algorithm and the optimal iteration algorithm provide an idea of determining the states of . From the idea, we obtain an algorithm for determining the states of based on the optimal iteration algorithm. In the algorithm, the variable iteration step is introduced; thus, we present an algorithm for determining the states of based on the variable iteration step. The presented algorithm accurately determines the states of . On the basis of these algorithms, we build a biproportional construction theory. The theory consists of a first and a second proportional construction theory. The former correctly calculates the FCs of at the present sampling time

Calculation of Mass Concrete Temperature Containing Cooling Water Pipe Based on Substructure and Iteration Algorithm

Mathematical physics equations are often utilized to describe physical phenomena in various fields of science and engineering.One such equation is the Fourier equation,which is a commonly used and effective method for evaluating the effectiveness of temperature control measures for mass concrete.One important measure for temperature control in mass concrete is the use of cooling water pipes.However,the mismatch of grids between large-scale concrete models and small-scale cooling pipe models can result in a significant waste of calculation time when using the finite element method.Moreover,the temperature of the water in the cooling pipe needs to be iteratively calculated during the thermal transfer process.The substructure method can effectively solve this problem,and it has been validated by scholars.The Abaqus/Python secondary development technology provides engineers with enough flexibility to combine the substructure method with an iteration algorithm,which enables the creation of a parametric modeling calculation for cooling water pipes.This paper proposes such a method,which involves iterating the water pipe boundary and establishing the water pipe unit substructure to numerically simulate the concrete temperature field that contains a cooling water pipe.To verify the feasibility and accuracy of the proposed method,two classic numerical examples were analyzed.The results showed that this method has good applicability in cooling pipe calculations.When the value of the iteration parameterαis 0.4,the boundary temperature of the cooling water pipes can meet the accuracy requirements after 4∼5 iterations,effectively improving the computational efficiency.Overall,this approach provides a useful tool for engineers to analyze the temperature control measures accurately and efficiently for mass concrete,such as cooling water pipes,using Abaqus/Python secondary development.

Identification of Lubricating Oil Additives Using XGBoost and Ant Colony Optimization Algorithms

To address the problem of identifying multiple types of additives in lubricating oil,a method based on midinfrared spectral band selection using the eXtreme Gradient Boosting(XGBoost)algorithm combined with the ant colony optimization(ACO)algorithm is proposed.The XGBoost algorithm was used to train and test three additives,T534(alkyl diphenylamine),T308(isooctyl acid thiophospholipid octadecylamine),and T306(trimethylphenol phosphate),separately,in order to screen for the optimal combination of spectral bands for each additive.The ACO algorithm was used to optimize the parameters of the XGBoost algorithm to improve the identification accuracy.During this process,the support vector machine(SVM)and hybrid bat algorithms(HBA)were included as a comparison,generating four models:ACO-XGBoost,ACO-SVM,HBA-XGboost,and HBA-SVM.The results showed that all four models could identify the three additives efficiently,with the ACO-XGBoost model achieving 100%recognition of all three additives.In addition,the generalizability of the ACO-XGBoost model was further demonstrated by predicting a lubricating oil containing the three additives prepared in our laboratory and a collected sample of commercial oil currently in use。

二阶Radon-Fourier变换与遗传算法结合的快速相参积累算法

针对匀加速运动的高速目标,可以用二阶Radon-Fourier变换(Second-order Radon-Fourier Transform,SRFT)完成对回波信号的相参积累。SRFT算法的原理是通过“速度-加速度”联合搜索来实现目标的运动参数估计,其计算量较大,不满足实时检测的需求。针对这个问题,提出一种基于遗传算法(Genetic Algorithm,GA)的快速实现方法。首先对运动参数集进行编码,设置初始群体;然后通过遗传算法对群体更新迭代,使其能够自发快速地逼近全局最优解,减少不必要的搜索路径;最终快速实现待检测目标的相参积累。仿真结果表明,在保证检测性能的前提下,算法计算量得到有效改善,运算次数减少大约一个量级。

基于Fourier拟合的光伏跟踪系统设计

[目的]为提高光伏支架的发电效率,以基于Fourier拟合算法的视日运动轨迹光伏跟踪器为研究设计对象。[方法]借助MATLAB分析了传统视日运动轨迹算法的跟踪精度情况,更进一步地在此基础上提出了精度更优的8阶傅里叶拟合视日运动轨迹跟踪算法,并结合GNSS定位技术,得出太阳实时运行轨迹。系统设计以STM32单片机作为微处理器,采用6轴加速度传感器,通过重力矢量在其轴上的投影确定光伏跟踪支架的实时倾斜度,以此二者建立跟踪支架三维运行模型,通过分析太阳光线在支架上的余弦效应即可得到电机需要运行的动作角。同时为解决晨昏时刻光伏组件间的阴影遮挡问题,系统增加逆跟踪算法。并考虑到大规模机组的应用,提出主从电机同步控制策略。[结果]傅-2里叶拟合算法拥有更高的跟踪精度,精度可达到10数量级,高于传统算法一个数量级。同时采用逆跟踪技术可节约24.3%光伏阵列用地面积,大幅提高了土地利用率。[结论]本研究采用更为精准的视日运动轨迹跟踪模型,较好地解决了太阳辐射利用的余弦效应,提升了电站的发电效率,实现了安全高效绿色能源体系的建设,促进了我国“双碳”目标的推进与达成。

基于Fourier-Mellin算法的干涉图像配准

提出了采用Fourier-Mellin算法对大孔径静态干涉成像光谱仪的原始干涉图像进行配准的方法,用于校正由于推扫平台系统姿态不稳所造成的失真。采用Fourier-Mellin算法和相位相关算法求取干涉图像的旋转角度和缩放及平移参数,并通过多帧未校正的图像和校正后的图像分别拼接成大面积地域图像来验证算法。实验结果表明,通过人眼判断,可以实现对图像的配准,配准精度达到1 pixel,基本满足将LASIS原始干涉图校正为不失真图像的要求。

复指数Fourier神经元网络隐神经元衍生算法

以平方可积空间上的复指数Fourier级数作为激励函数构造了新型Fourier神经元网络,并推导出采用加号逆表示的网络权值直接确定公式,克服了传统BP神经网络收敛速度慢、易陷于局部极小点、迭代学习易发生振荡等缺陷。并在此基础上构造了隐神经元衍生算法,克服了传统BP神经网络难以确定最优网络拓扑结构的缺点。理论分析及仿真实验表明,该复指数Fourier神经元网络能够一步计算网络最优权值且能自适应调整网络结构,对随机加性噪声具有抑制作用,并能高精度逼近非连续函数。

忆阻Fourier神经网络在图像复原中的应用

将传统Fourier神经网络与忆阻器相结合,用忆阻器做突触,构建新型的忆阻Fourier神经网络.推导忆导变化与权值更新的关系,提出忆阻突触权值更新规则,构建单输入忆阻Fourier神经网络,提出忆阻BP算法对模糊二值图像和灰度进行处理.Matlab仿真实验表明该算法可以有效实现图像复原,提高图像清晰度.忆阻Fourier神经网络有望用于解决复杂的图像处理问题.

基于半波Fourier算法的故障选相控制系统的设计

为了快速、准确地预测故障电流零点,设计了故障选相控制系统。基于故障选相原理,以数字信号处理器(DSP)TMS320F2812为核心,通过丰富其外设,进行控制系统硬件的设计;基于相电流突变量原理和改进半波Fourier算法,进行了故障起始时刻的判断和波形恢复,并完成了控制系统的软件设计。对故障选相控制系统的稳定性和零点预测准确度进行了测试。测试结果表明,控制器的预测结果准确、可靠,零点的预测时间<12ms,零点预测误差的3σ(σ为标准差)范围为[-0.6,0.6]ms,满足国际大电网会议(CIGRE)对选相投切控制系统准确度的要求。

SVM与Fourier算法在电网短期负荷预测中的应用

将Fourier(傅立叶)算法与SVM(支持向量机)共同引入电网短期负荷预测。对于波动性较大的负荷,Fourier算法用于滤除高次谐波分量。SVM用于对滤除了高次分量的数据进行统计学习,它首先筛选与预测点相关的历史数据构成训练样本,再将预测的平滑性和误差损失函数相结合构成问题的目标函数进行求解。编制了相应的软件,对某实际电网进行了短期负荷预测,取得了理想的结果。

量子Fourier变换在实现Deutsch-Jozsa算法中的应用

提出利用量子Fourier变换解决Deutsch-Jozsa算法问题的观点.结合量子Fourier变换和DeutschJozsa算法的量子电路,找到一种利用量子Fourier变换解决Deutsch-Jozsa算法新的量子电路,并考察该量子电路中各个线路的量子状态,结合算法对该量子线路的状态进行研究.结果表明:利用量子Fourier变换解决Deutsch问题,能够有效地提高运算速度,节省运算时间.

基于分数阶Fourier变换和ESPRIT算法的LFM信号2D波达方向估计

提出一种利用分数阶Fourier变换(FRFT)和旋转不变子空间(ESPRIT)算法实现多个线性调频(LFM)信号二维波达方向(DOA)估计的新方法。该方法利用FRFT对LFM信号的能量聚集特性,构造出一种新的FRFT域的阵列数据模型,并利用ESPRIT算法实现对多个LFM信号的二维DOA估计。仿真实验验证了算法的有效性。

基于多项式调频Fourier变换的信号分量提取方法

为了从含有噪声的混合信号中有效提取各个信号分量,提出一种基于多项式调频Fourier变换的分量提取方法.通过研究Fourier变换和分数阶Fourier变换的信号能量积累方式及变换基函数的时频表示,提出利用时频平面上的多项式调频曲线族代替Fourier变换和分数阶Fourier变换的调频直线族,将变换的适用范围扩展到非线性调频信号.采用粒子群智能优化算法搜索调频曲线族的最优多项式参数,使混合信号中的某一分量在多项式调频Fourier域上能量谱集中.最后对能量谱集中的分量进行窄带滤波,并利用多项式调频逆Fourier变换重构信号分量.仿真实验结果表明,该方法不仅能够提取混合信号中的线性调频分量,还能够实现非线性调频分量的能量谱集中、信号分离和时频特征提取.

基于Fourier神经网络的图像复原算法

由于退化图像的点扩散函数难以准确确定,提出一种基于Fourier正交基函数的前向神经网络图像复原模型,该模型以一组Fourier正交基为隐层神经元的激励函数,根据误差传递算法进行权值修正,达到收敛目标。给出Fourier神经网络及其相应的衍生算法的图像恢复实现步骤。实验表明,该方法能较好地实现图像的复原。

基于Fourier-Mellin变换和Keren算法的改进运动估计算法

针对超分辨率图像重建中图像运动估计精度要求高,速度要求快的问题,对传统的基于Fourier-Mellin变换和Keren算法的运动估计方法做出以下改进:首先提取参考图像和待估计图像的边缘,从而避免了Fourier-Mellin变换的不足(对细节不明显的图像运动估计精度极差);由于只是用Fourier-Mellin变换进行粗估计,对角度估计精度要求不高,只需小于1°,因此在进行对数极坐标变换时,可以减少角度坐标和对数坐标的采样点数,大幅缩小了矩阵大小,提高了运动估计速度;由于先用Fourier-Mellin对待估计图像进行粗估计,Keren算法可以避开复杂的金字塔计算而只需一层估计,减少了运动估计时间。在VC++中的仿真实验表明,该方法有效地结合了Fourier-Mellin变换和Keren算法的优点,同时又提高了运动估计速度。经测试,用未改进的算法对328×500像素大小的两幅图像进行运算估计需要3.53s,而用改进的算法则只需要1.15s,大大提高了运动估计速度。