Using the Fourier transform to interpret oscilloscope data

• rwooduk
In summary, the largest column in the frequency domain display represents the peak to peak voltage of the waveform pictured above.
rwooduk
We have a waveform that is composed of several waves, maybe something like this:

If we Fourier transform the graph we get something like this:

My question is, does the value of the largest column represent the peak to peak voltage of the waveform pictured above?

rwooduk said:
We have a waveform that is composed of several waves, maybe something like this:
If we Fourier transform the graph we get something like this:
My question is, does the value of the largest column represent the peak to peak voltage of the waveform pictured above?

That's too simple. The peak value of the whole time domain signal will depend on the relative phases of the frequency components. That frequency domain display will be the actual values of the amplitudes of the components in volts. The DFT gives you an actual value and would not 'normalise' the scale unless you ask it to.

rwooduk
Many thanks for the reply! So although my OP was in simple terms (apologies I'm fairly new to this) it is correct?

I have 200+ snapshots (1ms) of data from our oscilloscope and I'm trying to use MATLAB using the Fourier transform to determine the pressure amplitude for each waveform. Similar to what is shown here:

https://uk.mathworks.com/help/examples/matlab/FFTOfNoisySignalExample_01.png

https://uk.mathworks.com/help/examples/matlab/FFTOfNoisySignalExample_02.png

https://uk.mathworks.com/help/matlab/ref/fft.html

I'm a little confused what you mean by "normalise", if you could give a few more comments it would be appreciated.

Last edited by a moderator:
rwooduk said:
I'm a little confused what you mean by "normalise",
I just meant scaled to bring the displayed maximum frequency domain value to, perhaps, the maximum time domain value. (For convenience, when the input range is inconveniently small, for instance.)
If you Google around the Fourier Transform (finding a link that suits you) the constants outside the transform do not depend on the maximum amplitude of the time function.

rwooduk
I see, that's great many thanks for the suggestions and your help!

What is the Fourier transform and how is it used to interpret oscilloscope data?

The Fourier transform is a mathematical tool that decomposes a signal into its individual frequency components. It is used to analyze and interpret complex waveforms obtained from an oscilloscope. By converting a time-domain signal into a frequency-domain representation, the Fourier transform allows for easier identification and analysis of individual frequency components present in the signal.

What are the benefits of using the Fourier transform for analyzing oscilloscope data?

The use of the Fourier transform allows for a more detailed understanding of the underlying frequencies present in a signal. This can aid in identifying and troubleshooting issues with electronic circuits and systems. It also allows for the removal of unwanted noise from a signal, making it easier to interpret and analyze.

What types of signals are best suited for analysis using the Fourier transform?

The Fourier transform is best suited for analyzing periodic signals, such as sine waves, square waves, and other regular waveforms. It can also be used for non-periodic signals, but the results may not be as accurate.

What are some common mistakes to avoid when using the Fourier transform to interpret oscilloscope data?

One common mistake is using the Fourier transform on non-stationary signals. This can result in inaccurate frequency analysis. It is also important to ensure that the sampling rate of the oscilloscope is high enough to accurately capture the signal's frequency components.

Are there any limitations to using the Fourier transform for interpreting oscilloscope data?

The Fourier transform assumes that the signal being analyzed is continuous and infinite. This may not be the case in real-world scenarios, leading to some limitations in its accuracy. Additionally, the Fourier transform cannot accurately analyze signals with a large number of harmonics or sharp discontinuities.

• Electrical Engineering
Replies
6
Views
3K
• Electrical Engineering
Replies
63
Views
5K
• Electrical Engineering
Replies
5
Views
631
• Electrical Engineering
Replies
1
Views
1K
• Electrical Engineering
Replies
7
Views
928
• Electrical Engineering
Replies
31
Views
10K
• Electrical Engineering
Replies
18
Views
3K
• Engineering and Comp Sci Homework Help
Replies
14
Views
2K
• Calculus and Beyond Homework Help
Replies
1
Views
955
• Calculus and Beyond Homework Help
Replies
2
Views
1K