# Frequency correlation between two non stationary signals

• serbring
In summary, A person has measured the torque and speed of a shaft running at variable speed. They have noticed torque fluctuations and suspect that the frequency of the fluctuations is the same as the shaft speed. They need to use signal statistics functions to verify this. However, they are unsure about what to do with two non-stationary signals. They ask if they should use a different model or eliminate a variable in the experiment. Another person suggests using FFT or STFT to analyze the signals. The person confirms that the speed variation is not periodic and thanks the other person for their reply.
serbring
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

(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.

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

Last edited:

## 1. What is the definition of frequency correlation between two non-stationary signals?

The frequency correlation between two non-stationary signals is a measure of how similar the frequency content of the two signals is. It is a statistical metric that quantifies the degree of correlation between the frequencies present in each signal.

## 2. How is frequency correlation calculated for non-stationary signals?

Frequency correlation is typically calculated using a mathematical technique called cross-correlation. This involves multiplying the Fourier transforms of the two signals and then taking the inverse Fourier transform of the result. The magnitude of the resulting signal represents the frequency correlation between the two signals.

## 3. What is the difference between frequency correlation and time-domain correlation?

Frequency correlation looks at the similarity of frequency content between two signals, while time-domain correlation looks at the similarity of the signals in the time domain. Frequency correlation is useful for analyzing non-stationary signals, while time-domain correlation is more commonly used for stationary signals.

## 4. Can frequency correlation be used to determine causality between two signals?

No, frequency correlation does not imply causality between two signals. It only measures the degree of similarity in frequency content. To determine causality, additional analysis and experimentation is needed.

## 5. How can frequency correlation be applied in real-world scenarios?

Frequency correlation can be used in various fields such as signal processing, communications, and neuroscience. It can help in identifying patterns and relationships between signals, detecting anomalies or abnormalities, and improving signal processing techniques.

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