How to plot ifft for a frequency signal?

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Priyom Goswami
Priyom Goswami el 5 de Ag. de 2021
Comentada: Yazan el 6 de Ag. de 2021
I've a .dat file (attaching the .mat file of that .dat file after converting, since this platform doesn't allow to upload .dat file while asking question) which represent the frequency spectrum of a vibration signal from a bearing having a sampling frequency of (fs=32768). How to convert the frequency signal to time domain signal. Please help.
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Priyom Goswami
Priyom Goswami el 6 de Ag. de 2021
that is what i'm unable to do so.
Scott MacKenzie
Scott MacKenzie el 6 de Ag. de 2021
Editada: Scott MacKenzie el 6 de Ag. de 2021
Have you tried? Please post the code you've attempted so far.

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Respuesta aceptada

Yazan
Yazan el 6 de Ag. de 2021
Editada: Yazan el 6 de Ag. de 2021
clc, close all
fs = 32768;
fidx = z.Date23122013;
specOneSide = z.Time100351;
[fidx, idx] = unique(fidx);
specOneSide = specOneSide(idx);
fOneSide = (fidx./fidx(end))*fs/2;
subplot(1,2,1)
plot(fOneSide, specOneSide), xlabel('Frequency - Hz'), ylabel('Magnitude spectrum');
axis tight, title('One-sided spectrum');
specTwoSide = [flip(specOneSide(1:end)); specOneSide(2:end-1)];
N = length(specTwoSide);
f = -fs/2:fs/N:fs/2-fs/N;
subplot(1,2,2)
plot(f, specTwoSide), xlabel('Frequency - Hz'), ylabel('Magnitude spectrum');
axis tight, title('Two-sided spectrum');
sig = ifft(fftshift(specTwoSide));
figure,
t = (0:N-1)./fs;
plot(t, sig), axis tight, title('Signal');
xlabel('Time - sec'), ylabel('Amplitude');
  5 comentarios
Priyom Goswami
Priyom Goswami el 6 de Ag. de 2021
Thank You soo much. But i think there is something wrong with the data generated. Anyways, thank you once again.
Yazan
Yazan el 6 de Ag. de 2021
Notice that the values of the Date23122013 (or your frequency axis points) are not unique. Also, for one value of Date23122013, you have sometimes multiple values of Time100351. My code uses the first appearing value of Time100351 for a given Date23122013 automatically, which is sometimes zero, but you might prefer otherwise. It is always a good idea to clean your data first.

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