基波分量

文中指出，要满足检测器与故障讯号源参数匹配，必须以桥臂反压的基波分量作为检测对象。

It is shown that the fundamental components of the reverse voltage across the bridge arms must be taken as an object to be detected if the parameter matching between the fault detector and the signal source is to be realized .

通过对现阶段广泛采用的数字滤波算法进行比较分析，采用改进全波傅氏算法（IFFT）提取短路电流的基波分量，并给出了相应的数学推导及MATLAB仿真结果。

After analyzing and comparing digital filtering arithmetic , the Improved Fourier Transformations ( IFFT ) is adopted to separate the fundamental component of short current . Furthermore , the corresponding arithmetic derivations and simulation results under MATLAB are given .

离散傅里叶变换（DFT）在电参量检测领域应用十分广泛，其算法基本原理是利用离散傅里叶变换抽取基波分量，计算出电参量参数。

The discrete Fourier transform ( DFT ) is widely used in the field of electrical parameters detection .

解答由主部x0（只包含一个基波分量）和一、二阶修正量x1、x2（三次、五次谐波分量及基波分量的修正量）组成。

The solution is composed of the main oscillation x0 ( includes one resonant-frequency component only ) and 1st - , 2nd-order corrections x1 , x2 ( 3rd , 5th harmonics and correction of the fundamental-frequency component ) .

以MCU+浮点型DSP为硬件核心，软件上采用加窗、插值的高精度FFT算法，提高了非同步采样时泄漏电流中阻性电流基波分量的测试精度。

Based on the hardware of MCU and floating DSP , the software utilizes the windows and interpolated FFT algorithm , which can improve the measure precision of fundamental frequency component of resistive leakage current caused by unsynchronized sampling .

MOA阻性电流检测的关键在于电压基波分量与泄漏电流基波分量相位差的检测。

The key to the detection of MOA resistive current is the detection of the phase difference between fundamental component of voltage and fundamental component of leakage current .

利用Hilbert-Huang变换分析非平稳信号的优势，对断电后的零序电压进行了经验模态分解（EMD），提取出基波分量。

Using the superiority of Hilbert-Huang Transformation in the non-steady signal analysis , the fundamental zero sequence voltage after switch off is extracted by empirical mode decomposition ( EMD ) .

DVR的检测方法与谐波、无功电流的检测不同，不但需要检测出除基波分量之外的总畸变分量，还要检测出基波分量与基波基准值之差。

The detecting method of DVR is different from harmonic and reactive current detecting methods . It need detect not only total harmonic distortion but also the difference between fundamental wave component and reference value .

针对在配变监控终端中通过傅里叶算法从电力信号获得基波分量耗时长的问题，提出了通过FIR滤波可对电流互感器进行相位补偿的快速算法，并在运行中得以应用。

To solve the problem to take a long time to gain fundamental wave from electric signal in distribution transformer terminal unit by Fourier algorithm , the fast algorithm which can compensate CT phase by FIR filter is presented . The algorithm is used in operation .

确定了计算所需的阶数，然后在考虑噪声的基础上直接计算CVT暂态信号中的基波分量，不需要知道任何CVT参数，仅用一个周波左右的时间即可得到正确的值。

Then , with considering the noise , the fundamental value in transient signal of CVT is calculated directly which could achieve the correct value in about one fundamental cycle . No parameter of CVT is needed in the whole process .

对MOA交流伏安特性进行分析，发现随着电压升高，阻性电流谐波分量增长幅度明显比基波分量增长幅度大，但阻性电流基波分量增长稳定。

Through the analysis of MOA AC V-I characteristics , it is found that with voltage increasing , the harmonic contents of resistive current is increasing bigger than that of first-harmonic , and the increasing of the magnitude of first-harmonic is well-proportioned .

根据模型化测量的思想，使用高斯-牛顿（Gauss-Newton）优化算法计算电压基波分量的参数，并进行了仿真。

And according to modeling measurement , we detect real-time data ( amplitude frequency phase angle ) of fundamental component of the line voltage based on optimality algorithm ( Gauss-Newton ) . Besides , the algorithm emulation is presented .

还提出了基于稳健回归算法的直流分量辨识算法，以及基于Hilbert变换和非线性变量优化（NLO）的基波分量辨识算法，实现了同步电机瞬态和超瞬态参数的精确辨识。

In addition , this article presents a technique using robust regression algorithm to analysis the DC current component , as well as a new algorithm based on Hilbert and NLO for the analysis of fundamental current component , consequently , realizes accurate identification of transient and subtransient parameters .

用对称分量法检测间谐波背景下的基波分量

A Method to Detect Fundamental Component by Symmetrical Component under Inter-Harmonics

一种电网电压基波分量的实时检测方法

A real-time method for detecting the fundamental component of line voltage

一种提取基波分量的高精度快速滤波算法

Accurate and Fast Filtering Algorithm for Fundamental Component

一种测量电信号基波分量的快速算法

A Fast Algorithm for Measurement of Fundamental

故障距离越远，电流、电压中的谐波含量对基波分量的影响越大；

The farther the fault location is , the larger the HF component will be .

它可以检测变频调速系统中电流、电压基波分量的瞬时值、平均值和功率因数角。

The instantaneous value and mean value of basic wave current and voltage can be measured with this method .

该方法使用一固定宽度窗口内的电网电压数据来估算其基波分量的幅值和相位。

Voltage data within a fixed width window are used to estimate the amplitude and phase of the fundamental component .

提出了一种在电网电压畸变情况下依然适用的电网电压基波分量的实时检测方法。

A real time method for detecting the fundamental component of the line voltage under distorted circumstance is proposed in the paper .

由计算机数值分析给出的基波分量大小，得到了激光频率的灵敏鉴别。

Analysis by use of computer gives sensitive detection of the fundamental frequency component and the laser frequency sensitive discrimination is obtained .

周期函数模型算法分为全周波傅氏算法和半周波傅氏算法，最适合微机保护计算基波分量。

Algorithms based on periodic function model contain full-cycle fourier algorithm and half-cycle fourier algorithm and are adapt to extracting the fundamental component .

存在分数次谐波时，差分滤波求得基波分量幅值和相角的误差最小。

The error of fundamental component and phase angle calculated by means of differential algorithms is the minimum value when fractional harmonic exists .

再经过变换得到原电流的基波分量，从原电流中减去基波分量得到要检测的谐波分量。

The fundamental current can be reconstructed by transformation while the harmonic current can be gained by subtracting fundamental components from the original current .

电压和电流的基波分量采用全波移动均值提取傅里叶级数基波序分量的方法得到。

The fundamental values of the voltage and current are got based on Fourier series extraction of fundamental sequence components using one cycle moving averaging .

分析了冷轧带钢轧机偏心补偿控制的机理，建立了通过傅立叶分析提取偏心信号基波分量作为控制量的偏心补偿动态结构图。

Based on eccentricity control principle and eccentricity signal model , an eccentricity compensation project for single stand and reversing cold strip mill was studied .

且光谱基波分量及低次谐波分量的贡献依赖于粒子直径、标准偏差及相对折射率的大小。

The contributions of wave component of different orders are dependence on the mean diameter , size distribution and relative refractive index of the particles .

该算法理论上可以完全消除任意衰减时间常数τ的非周期分量对基波分量的影响。

With the algorithm the influence of an exponential DC component on the fundamental wave component of random decreasing time consent τ can be completely eliminated .

仿真还验证了移动数据窗傅里叶滤波的性能，能高精度和快速地获得故障数据中的基波分量。

Meanwhile , the simulation results demonstrated that the mobile data window Fourier filter can obtain the fundamental component from fault data with rapidity and high-precision .