Frequency correlation between two non stationary signals

AI Thread Summary
The discussion centers on analyzing torque and speed measurements from a shaft running at variable speeds. The user suspects that torque fluctuations correlate with the shaft speed and seeks methods to verify this using signal statistics. Since the speed variation is non-periodic, traditional methods like PSD may not apply directly. Suggestions include using the short-time Fourier transform (STFT) or wavelet transform for time-dependent analysis. These methods can help identify frequency components in the non-stationary signals effectively.
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Hi all,

I have measured the torque and the speed of a shaft when running at a variable speed. From the measurements, torque fluctuations are in the torque signals and I have the feeling that the fluctuations frequency is the shaft speed. I need to verify this with some signal statistics functions. In case the shaft speed would have been constant, I would have computed the PSD of the torque signal and I would have compared its peak frequency with the shaft speed. But what should I do with two non stationary signals?

Thanks
 
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(a) use a different model
(b) eliminate a variable in the experiment
 
Is the speed variation itself periodic?

If yes, you can still use FFT on the whole signal and you will just get another peak for the frequency of speed variation.

You could also try a short-time Fourier transform (STFT) or wavelet transform if you wish to analyze the signals as a function of time as well.
 
Hi Boneh3ad,

thanks for youre reply. The speed variation is not periodic. I may try the STFT, thanks
 
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