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Using the Fourier transform to interpret oscilloscope data

  1. Nov 30, 2016 #1
    We have a waveform that is composed of several waves, maybe something like this:

    original.jpg

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

    zhGVrnz.jpg

    My question is, does the value of the largest column represent the peak to peak voltage of the waveform pictured above?
     
  2. jcsd
  3. Nov 30, 2016 #2

    sophiecentaur

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    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.
     
  4. Nov 30, 2016 #3
    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 [Broken]

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

    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: May 8, 2017
  5. Nov 30, 2016 #4

    sophiecentaur

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    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.
     
  6. Nov 30, 2016 #5
    I see, that's great many thanks for the suggestions and your help!
     
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