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FFT of Voltage Waveform... (Check my work)

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Glenn0010:
Hi All,

Thank you a lot for your help! I clearly was very rusty on this stuff. So taking you advice I have done some changes.

Unfortunetly I am furloughed so I cannot get any scope data, however what I've done is I've created a waveform from the trun on and turn off edge. Then I've copied this to create three cycles.

This gives me the following results (I am still getting a peak at the very end of the freq domain butI have limited the x axis here.)





The first harmonic i sat 366210 Hz which is the switching frequency as I was limited by excel to 4096 points.

We can see the odd and even harmonics of it there.

So here is the full frequency domain



and

here is the end peak zoomed



Are these harmonics related to the switching transitions as I'd expect them to be at higher frequencies although maybe not so high.

There is also this section of low amplitude in the middle here, which maybe due to the jitter of the switching transitions? I am thinking this since the jitter is quite low in amplitude.



What I am trying to do with this is to recreate the noise spectrums (EMI) from double pulse test data as it would really speed up our testing if we can estimate a good spectrum at the pulse testing stage. I am trying to follow the method shown in the paper "Characterization of Power Electronics EMI Emission" by Chingchi CHEN which can be found on IEEE It shows how this spectrum can be quite accuratley predicted from the harmonics, so getting the harmonics right is the very first step.

Any thoughts? thanks again for your help.

Dr. Frank:
I just tested the excel FFT function with a square wave, and found out that the output is mirrored / doubled, so you can discard the 2nd half of the frequency domain output. The last dip on the rightmost end with amplitude 500 represents again the 1st harmonic, mirrored.

Generally, when you have for example 256 time domain input data (e.g. samples from your A/D), the FFT delivers only 128 valid frequency domain output data, also due to the Nyquist theorem. The first one is the DC component, followed by the 1st up to the 127th harmonics.   

Frank

Mechatrommer:
yes, FFT output needs to be post-processed, cut into half. the other half is just mirror. so if you are processing 1000 points, the only usefull points in FFT is the first 500 points, the other is dummy mirror.

gf:
I suggest that you try a logarithmic scale for the y axis (e.g. 20*log10(y)).
From your new data (using a hannig window) I get



(scale of y-axis is normalized to 0dB for the frequency with the highest amplitide)

Your harmonics decay faster than for an ideal square wave. At about 15 MHz they drown in the noise floor.
As you noticed yourself, there are signal components in the 210..250 MHz range which stick out from the noise floor, too. I guess they are caused by the ringing/oscillation (1) at the rising/falling edges of your pulses. But since they are close to fs/2, and even increase towards fs/2, I'm also wondering whether the sampling theorem was obeyed, so I'm rather reluctant regarding too many speculations. At least for comparison, you should try to sample them at a higher rate.
There is also a small peak near ~27MHz which I can' associate with anything yet.
The manual stitching of (equal) waveform fragments may have disturbed the results either to some extent (-> add discontinuities, make sampled noise correlated, on the other hand add some noise-free segments (which were noisy in reality), no jitter,...). You should really try to sample a couple of periods from the real signal.

EDIT:

(1) Zoom-in: Ringing/oscillation at edge of your pulse



Looks indeed as if the sampling rate might not suffice to capture the fast oscillation.

Mechatrommer:
after much fondling with your data, this is what i come up with.. much like a fabricated data rather than real data.

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