MATLAB: Error getting Fourier transform of a 1d signal

fftfourier transformMATLAB

Hello,

I have an almost-sinusoidal signal (see attached file), which I believe is composed of a mixture of maybe 2 (or 3) Fourier modes:

I wanted to verify this by plotting its Fourier transform. I expected a flat signal with a bunch of peaks at the signal harmonics. However, using fft() on the signal gives me a 2d plot that makes absolutely no sense to me. Can someone please help me to understand what is going on?

Best Answer

The easiest way to determine the location of the peaks is to use the findpeaks function (with the appropriate name-value pairs to isolate your peaks of interest). I cannot guarantee that the frequencies will be integer multiples of each other, however findpeaks is the best way to identify them.

Improve the frequency resolution by increasing the length of the fft itself. Specify an appropriately large value for ‘n’ (the second argument) to increase the frequency resolution to whatever you want.

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MATLAB: How to obtain Fourier power spectrum of velocity data

See if the pwelch (link) function will do what you want. It may also not show any specific frequency peaks (it tends to combine closely-spaced peaks), however it will do essentially everything you describe as what you want to do.

MATLAB: Is the fundamental frequency at the 15th harmonic order

I am not certain what you are doing, or what result you want.

One problem is that you also need to specify the x-values of the bars in your bar call:

bar(Fv(1:20), har_mag(1:20),0.4)

If you want to find all the relevant peaks and their frequencies, add these lines after your existing (posted) code:

[pks,locs] = findpeaks(har_mag, 'MinPeakProminence',0.5);
FreqPeaks = table(Fv(locs)', pks, 20*log10(pks), 'VariableNames',{'Freq', 'Amp', 'dB'})
figure
plot(Fv, 20*log10(har_mag))
hold on
plot(Fv(locs), 20*log10(har_mag(locs)), '+r')
hold off
grid
axis([0  1200    -15  60])

The ‘FreqPeaks’ table has all the identified peaks (linear and dB) and their associated frequencies.

Best Answer

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