FFT plot accuracy & Scaling

15 次查看（过去 30 天）

Bledar Ferati 2020-12-8

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/687068-fft-plot-accuracy-scaling

编辑： VBBV 2020-12-9

Currently struggling on knowing whether my fft plot is entirely accurate. Trying to also achieve the correct scaling as well. I have looked at a lot of posts regarding this but still not achieving the same sort of scale. I am trying to achieve this:

But I am getting this:

Fs = 5000/157
data = x
L = length(data)
Y = fft(data)/L
f = Fs/2*linspace(0,1,L/2+1);
plot(f,2*abs(Y(1:L/2+1)))
xlim([0.08 0.78])
set(gca, 'YScale', 'log')
title('Duffing')
xlabel('f (Hz)')
ylabel('Amplitude')

Any help would be much appreciated

9 个评论
显示 7更早的评论隐藏 7更早的评论

Mathieu NOE 2020-12-8

在 MATLAB Online 中打开

FYI, this is my fft / averaging / scaling function - please use it as you like :

  function  [freq_vector,fft_spectrum] = myfft_peak(signal, Fs, nfft, Overlap)
    %FFT peak spectrum of signal  (example sinus amplitude 1   = 0 dB after fft).
    %   signal - input signal, 
    %   Fs - Sampling frequency (Hz).
    %   nfft - FFT window size
    %   Overlap - buffer overlap % (between 0 and 0.95)
    samples = length(signal);
    % fill signal with zeros if its length is lower than nfft
    if samples<nfft
        s_tmp = zeros(nfft,1);
        s_tmp((1:samples)) = signal;
        signal = s_tmp;
    end
    % window : hanning
    window = hanning(nfft);
    window = window(:);
%    compute fft with overlap 
     offset = fix((1-Overlap)*nfft);
     spectnum = 1+ fix((samples-nfft)/offset); % Number of windows
%     % for info is equivalent to : 
%     noverlap = Overlap*nfft;
%     spectnum = fix((samples-noverlap)/(nfft-noverlap));	% Number of windows
        % main loop
        fft_spectrum = 0;
        for i=1:spectnum
            start = (i-1)*offset;
            sw = signal((1+start):(start+nfft)).*window;
            fft_spectrum = fft_spectrum + (abs(fft(sw))*4/nfft);     % X=fft(x.*hanning(N))*4/N; % hanning only 
        end
        fft_spectrum = fft_spectrum/spectnum; % to do linear averaging scaling
    % one sidded fft spectrum  % Select first half 
        if rem(nfft,2)    % nfft odd
            select = (1:(nfft+1)/2)';
        else
            select = (1:nfft/2+1)';
        end
    fft_spectrum = fft_spectrum(select);
    freq_vector = (select - 1)*Fs/nfft;
  end

Bledar Ferati 2020-12-8

Yeah thats what I was thinking as well, in terms of accuracy its pretty much there anyways. Thank you all for the help!

VBBV 2020-12-9

编辑：VBBV 2020-12-9

在 MATLAB Online 中打开

%true
L = max(data)
f = (Fs/2)*linspace(0,1,L)
plot(f(1:L:end), 2*abs(Y(1:L:end)))

Use max value of data instead of length

请先登录，再进行评论。

请先登录，再回答此问题。

回答（0 个）

请先登录，再回答此问题。

类别

Signal Processing Signal Processing Toolbox Digital and Analog Filters Multirate Signal Processing

在 Help Center 和 File Exchange 中查找有关 Multirate Signal Processing 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by

FFT plot accuracy & Scaling

9 个评论
显示 7更早的评论隐藏 7更早的评论

回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

FFT plot accuracy & Scaling

9 个评论 显示 7更早的评论隐藏 7更早的评论

回答（0 个）

另请参阅

类别

标签

Community Treasure Hunt

9 个评论
显示 7更早的评论隐藏 7更早的评论