Tab.2 Relative errors of fundamental frequency with frequency changing of fundamental 由表2可见,在基波频率波动影响下,常规混合基FFT算法和补零FFT算法已经失准,本文算法的测量相对误差整体稳定在10-5%以下。 在不同基波频率下,采用本文算法对各次谐波幅值进行测量分析,得到各次谐波幅值的相对误差如图6所示。
As mentioned, Fourier analysis transforms signals from the time domain to the frequency domain. But more correctly, FFT analysis is a mathematical method for transforming a finite time function \(a(t)\) of \(N\) equally spaced time samples into a function of frequency \(A(f)\) of \(N...
2.A harmonic measuring approach based on windows and interpolated FFT and dymamic frequency基于加窗插值FFT和动态频率的谐波检测算法 3.The Rife-Vincent(Ⅲ) window interpolation FFT algorithm by using cubic spline function基于三次样条函数的加Rife—Vincent(Ⅲ)窗FFT插值算法 4.Blackman-harris window inte...
It involves the calculation of an interpolated FFT spectrum (S′) of correlated signals in which the frequency lines corresponding to half-integer values of the frequency resolution defined by the FFT are obtained by a combination of both amplitude and phase values of the FFT spectrum (S)....
(fs/2);%define tansition bandwidth M=round(8/mm);%define the window length NN=M-1;%define the order of filter b=fir1(NN,1*f1/(fs/2));%use the firl function to design a filter [h,f]=freqz(b,1,512);%amplitude-frequency characteristic graph plot(f*fs/(2...
Output is equal amplitude sine waves at each frequency bin of the measurement span. Measured spectra (all spans, Source Cal on) <0.05 dB pk-pk (typical), <0.2 dB pk-pk (max), Amplitude=1.0 Vpk. Auto Phase function calibrates to current phase spectrum. Monochrome CRT. 640H by 480V ...
and an Inverse FFT layer. The FFT for training facilitates the interaction of information in the frequency domain for the input single-cell data. At the same time, the weighted gating layer employs trainable weight parameters to determine the frequency weights within the FFT encoding layer. In sc...
电气设备绝缘介质损耗角(介损角)的实时检测,可以为设备的绝缘监测提供可靠依据。采用FFT算法进行介损角测量时,因非同步采样会造成频谱泄漏,从而影响介质损耗角的测量精度。笔者分析了FFT算法的频谱泄漏效应,在此基础上采用了5点加权FFT算法实现对介损角的检测。该算法对
(1), for computing a single X(k) spectral value based on N FFT samples, where frequency k is not an integer. Equation (1) is not valid and I showed why that is so. (I remain troubled by this and perhaps someone can prove me wrong.) Next I presented four different expressions, Eq...
ylabel('Frequency') plt.show() In the last histogram above, the first 50 coefficients are ignored. In most of the cases, the value of the first co-efficient magnitude is way higher than the others and it contains a lot more information compared to the others. The last co-efficient in ...