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    <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/168623</link>
    <title>MATLAB Central Newsreader - FFT - Output to RMS Equivalents</title>
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    <item>
      <pubDate>Sun, 04 May 2008 10:18:34 -0400</pubDate>
      <title>Re: FFT - Output to RMS Equivalents</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/168623#430147</link>
      <author>NZTideMan</author>
      <description>On May 3, 3:03=A0am, "John Costello" &amp;lt;JohnCoste...@ChampAero.com&amp;gt; wrote:&lt;br&gt;
&amp;gt; Dave&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Thanks for your update. =A0I am aware of the sqrt(2)&lt;br&gt;
&amp;gt; equivalence for a simple sinusoid with an RMS equivalent...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; what I am wrestling with at the moment is...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; a composite signal with a dc offset, and two extra (could&lt;br&gt;
&amp;gt; be more) sinuodal frequencies modulated (or superimposed)&lt;br&gt;
&amp;gt; on the dc carrier....&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; The output of the FFT algorithm produces a discrete number&lt;br&gt;
&amp;gt; of complex numbers corresponding to x + iy for each&lt;br&gt;
&amp;gt; frequency...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; The product of x + iy times its conjugate x - iy yields the&lt;br&gt;
&amp;gt; absolute value or magnitude squared....&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; so, when plotted as power (or the signal FFT squared)...&lt;br&gt;
&amp;gt; against frequency, I obtain a plot of a squared term vs.&lt;br&gt;
&amp;gt; frequency...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; For argument sake suppose the power coefficient of the&lt;br&gt;
&amp;gt; first major term in the plot occurs at 100 Hz and has an&lt;br&gt;
&amp;gt; amplitude of 10, the second major term occurs at 1 KHz and&lt;br&gt;
&amp;gt; has an amplitude of 5....&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Is there a simple mechanism for exracting the RMS&lt;br&gt;
&amp;gt; equivalents for the 100 Hz and 1 KHz content, equivalent&lt;br&gt;
&amp;gt; amplitude of the RMS signal for each of the discrete&lt;br&gt;
&amp;gt; frequencies? =A0Since I'm working with a squared relationship&lt;br&gt;
&amp;gt; between power (squared term) back to equivalent amplitude&lt;br&gt;
&amp;gt; of a voltage waveform for either 100 Hz or 1 KHz...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; Thanks for your input on this issue.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; cheers&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; John Costello&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; "Dave Robinson" &amp;lt;dave.robin...@somewhere.biz&amp;gt; wrote in&lt;br&gt;
&amp;gt; message &amp;lt;fvf8bn$pb...@fred.mathworks.com&amp;gt;...&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; "John Costello" &amp;lt;JohnCoste...@ChampAero.com&amp;gt; wrote in&lt;br&gt;
&amp;gt; &amp;gt; message &amp;lt;fvf4jm$4d...@fred.mathworks.com&amp;gt;...&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; I need some help converting the Matlab FFT output into&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; equivalent RMS levels for signal analysis.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; I have numerical data from an oscilloscope that has&lt;br&gt;
&amp;gt; three&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; primary frequencies: =A0these are a DC component and two&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; separate frequencies. =A0I can calculate the RMS of the&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; composite signal with a bit of integration and the use&lt;br&gt;
&amp;gt; of&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; the RMS defintion.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; The FFT routine identifies the equivalent power at the&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; discrete frequencies with the Matlab FFT algorithm. =A0I&lt;br&gt;
&amp;gt; am&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; plotting the frequency vs. the FFT * the conjugate of&lt;br&gt;
&amp;gt; the&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; FFT to obtain the power signal. =A0For the n point data&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; acquisition, I am doing the following to obtain the&lt;br&gt;
&amp;gt; power:&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; Y =3D fft(v,n);&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; Pyy =3D Y.*conj(Y)/n ;&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; Does someone out there know how to extract the&lt;br&gt;
&amp;gt; equivalent&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; RMS components of the other frequency content?&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; best regards&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; &amp;gt; J. Costello&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; Its late on Friday afternoon, so don't expect too much.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; Each component in the FFT spectrum represents (once you&lt;br&gt;
&amp;gt; &amp;gt; have taken into account any scaling caused by the FFT&lt;br&gt;
&amp;gt; &amp;gt; algorithm itself) the amplitude of the complex sinewave&lt;br&gt;
&amp;gt; &amp;gt; component. From memory there is a well known relationship&lt;br&gt;
&amp;gt; &amp;gt; between the amplitude and RMS value of a sine wave - (so&lt;br&gt;
&amp;gt; &amp;gt; well known I can't remember it;-) other than to say it&lt;br&gt;
&amp;gt; &amp;gt; contains good factors such as square-root of 2. So if you&lt;br&gt;
&amp;gt; &amp;gt; compute the amplitude rather than power spectrum I guess&lt;br&gt;
&amp;gt; &amp;gt; you can apply this scaling factor to each and every&lt;br&gt;
&amp;gt; &amp;gt; component frequency. I guess a simple bit of algebra will&lt;br&gt;
&amp;gt; &amp;gt; allow you to scale it so it applies equally well in the&lt;br&gt;
&amp;gt; &amp;gt; power domain.&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; Hope that helps&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; &amp;gt; Dave Robinson- Hide quoted text -&lt;br&gt;
&amp;gt;&lt;br&gt;
&amp;gt; - Show quoted text -&lt;br&gt;
&lt;br&gt;
&lt;br&gt;
A clue:&lt;br&gt;
The RMS value includes the DC or mean, whereas the amplitudes from the&lt;br&gt;
FFT exclude the mean ( it is in the zeroth frequency bin).&lt;br&gt;
</description>
    </item>
    <item>
      <pubDate>Fri, 02 May 2008 15:03:03 -0400</pubDate>
      <title>Re: FFT - Output to RMS Equivalents</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/168623#429945</link>
      <author>John Costello</author>
      <description>Dave&lt;br&gt;
&lt;br&gt;
Thanks for your update.  I am aware of the sqrt(2) &lt;br&gt;
equivalence for a simple sinusoid with an RMS equivalent...&lt;br&gt;
&lt;br&gt;
what I am wrestling with at the moment is...&lt;br&gt;
&lt;br&gt;
a composite signal with a dc offset, and two extra (could &lt;br&gt;
be more) sinuodal frequencies modulated (or superimposed) &lt;br&gt;
on the dc carrier....&lt;br&gt;
&lt;br&gt;
The output of the FFT algorithm produces a discrete number &lt;br&gt;
of complex numbers corresponding to x + iy for each &lt;br&gt;
frequency...&lt;br&gt;
&lt;br&gt;
The product of x + iy times its conjugate x - iy yields the &lt;br&gt;
absolute value or magnitude squared....&lt;br&gt;
&lt;br&gt;
so, when plotted as power (or the signal FFT squared)... &lt;br&gt;
against frequency, I obtain a plot of a squared term vs. &lt;br&gt;
frequency...&lt;br&gt;
&lt;br&gt;
For argument sake suppose the power coefficient of the &lt;br&gt;
first major term in the plot occurs at 100 Hz and has an &lt;br&gt;
amplitude of 10, the second major term occurs at 1 KHz and &lt;br&gt;
has an amplitude of 5....&lt;br&gt;
&lt;br&gt;
Is there a simple mechanism for exracting the RMS &lt;br&gt;
equivalents for the 100 Hz and 1 KHz content, equivalent &lt;br&gt;
amplitude of the RMS signal for each of the discrete &lt;br&gt;
frequencies?  Since I'm working with a squared relationship &lt;br&gt;
between power (squared term) back to equivalent amplitude &lt;br&gt;
of a voltage waveform for either 100 Hz or 1 KHz...&lt;br&gt;
&lt;br&gt;
Thanks for your input on this issue.&lt;br&gt;
&lt;br&gt;
cheers&lt;br&gt;
&lt;br&gt;
John Costello&lt;br&gt;
&lt;br&gt;
"Dave Robinson" &amp;lt;dave.robinson@somewhere.biz&amp;gt; wrote in &lt;br&gt;
message &amp;lt;fvf8bn$pb9$1@fred.mathworks.com&amp;gt;...&lt;br&gt;
&amp;gt; "John Costello" &amp;lt;JohnCostello@ChampAero.com&amp;gt; wrote in &lt;br&gt;
&amp;gt; message &amp;lt;fvf4jm$4df$1@fred.mathworks.com&amp;gt;...&lt;br&gt;
&amp;gt; &amp;gt; I need some help converting the Matlab FFT output into &lt;br&gt;
&amp;gt; &amp;gt; equivalent RMS levels for signal analysis.&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; I have numerical data from an oscilloscope that has &lt;br&gt;
three &lt;br&gt;
&amp;gt; &amp;gt; primary frequencies:  these are a DC component and two &lt;br&gt;
&amp;gt; &amp;gt; separate frequencies.  I can calculate the RMS of the &lt;br&gt;
&amp;gt; &amp;gt; composite signal with a bit of integration and the use &lt;br&gt;
of &lt;br&gt;
&amp;gt; &amp;gt; the RMS defintion.&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; The FFT routine identifies the equivalent power at the &lt;br&gt;
&amp;gt; &amp;gt; discrete frequencies with the Matlab FFT algorithm.  I &lt;br&gt;
am &lt;br&gt;
&amp;gt; &amp;gt; plotting the frequency vs. the FFT * the conjugate of &lt;br&gt;
the &lt;br&gt;
&amp;gt; &amp;gt; FFT to obtain the power signal.  For the n point data &lt;br&gt;
&amp;gt; &amp;gt; acquisition, I am doing the following to obtain the &lt;br&gt;
power:&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; Y = fft(v,n);&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; Pyy = Y.*conj(Y)/n ;&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; Does someone out there know how to extract the &lt;br&gt;
equivalent &lt;br&gt;
&amp;gt; &amp;gt; RMS components of the other frequency content?&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; best regards&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; J. Costello&lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; &amp;gt; &lt;br&gt;
&amp;gt; Its late on Friday afternoon, so don't expect too much.&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Each component in the FFT spectrum represents (once you &lt;br&gt;
&amp;gt; have taken into account any scaling caused by the FFT &lt;br&gt;
&amp;gt; algorithm itself) the amplitude of the complex sinewave &lt;br&gt;
&amp;gt; component. From memory there is a well known relationship &lt;br&gt;
&amp;gt; between the amplitude and RMS value of a sine wave - (so &lt;br&gt;
&amp;gt; well known I can't remember it;-) other than to say it &lt;br&gt;
&amp;gt; contains good factors such as square-root of 2. So if you &lt;br&gt;
&amp;gt; compute the amplitude rather than power spectrum I guess &lt;br&gt;
&amp;gt; you can apply this scaling factor to each and every &lt;br&gt;
&amp;gt; component frequency. I guess a simple bit of algebra will &lt;br&gt;
&amp;gt; allow you to scale it so it applies equally well in the &lt;br&gt;
&amp;gt; power domain.&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Hope that helps&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Dave Robinson&lt;br&gt;
&lt;br&gt;
</description>
    </item>
    <item>
      <pubDate>Fri, 02 May 2008 14:27:03 -0400</pubDate>
      <title>Re: FFT - Output to RMS Equivalents</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/168623#429937</link>
      <author>Dave Robinson</author>
      <description>"John Costello" &amp;lt;JohnCostello@ChampAero.com&amp;gt; wrote in &lt;br&gt;
message &amp;lt;fvf4jm$4df$1@fred.mathworks.com&amp;gt;...&lt;br&gt;
&amp;gt; I need some help converting the Matlab FFT output into &lt;br&gt;
&amp;gt; equivalent RMS levels for signal analysis.&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; I have numerical data from an oscilloscope that has three &lt;br&gt;
&amp;gt; primary frequencies:  these are a DC component and two &lt;br&gt;
&amp;gt; separate frequencies.  I can calculate the RMS of the &lt;br&gt;
&amp;gt; composite signal with a bit of integration and the use of &lt;br&gt;
&amp;gt; the RMS defintion.&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; The FFT routine identifies the equivalent power at the &lt;br&gt;
&amp;gt; discrete frequencies with the Matlab FFT algorithm.  I am &lt;br&gt;
&amp;gt; plotting the frequency vs. the FFT * the conjugate of the &lt;br&gt;
&amp;gt; FFT to obtain the power signal.  For the n point data &lt;br&gt;
&amp;gt; acquisition, I am doing the following to obtain the power:&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Y = fft(v,n);&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Pyy = Y.*conj(Y)/n ;&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; Does someone out there know how to extract the equivalent &lt;br&gt;
&amp;gt; RMS components of the other frequency content?&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; best regards&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; J. Costello&lt;br&gt;
&amp;gt; &lt;br&gt;
&amp;gt; &lt;br&gt;
Its late on Friday afternoon, so don't expect too much.&lt;br&gt;
&lt;br&gt;
Each component in the FFT spectrum represents (once you &lt;br&gt;
have taken into account any scaling caused by the FFT &lt;br&gt;
algorithm itself) the amplitude of the complex sinewave &lt;br&gt;
component. From memory there is a well known relationship &lt;br&gt;
between the amplitude and RMS value of a sine wave - (so &lt;br&gt;
well known I can't remember it;-) other than to say it &lt;br&gt;
contains good factors such as square-root of 2. So if you &lt;br&gt;
compute the amplitude rather than power spectrum I guess &lt;br&gt;
you can apply this scaling factor to each and every &lt;br&gt;
component frequency. I guess a simple bit of algebra will &lt;br&gt;
allow you to scale it so it applies equally well in the &lt;br&gt;
power domain.&lt;br&gt;
&lt;br&gt;
Hope that helps&lt;br&gt;
&lt;br&gt;
Dave Robinson&lt;br&gt;
</description>
    </item>
    <item>
      <pubDate>Fri, 02 May 2008 13:23:03 -0400</pubDate>
      <title>FFT - Output to RMS Equivalents</title>
      <link>http://www.mathworks.com/matlabcentral/newsreader/view_thread/168623#429927</link>
      <author>John Costello</author>
      <description>I need some help converting the Matlab FFT output into &lt;br&gt;
equivalent RMS levels for signal analysis.&lt;br&gt;
&lt;br&gt;
I have numerical data from an oscilloscope that has three &lt;br&gt;
primary frequencies:  these are a DC component and two &lt;br&gt;
separate frequencies.  I can calculate the RMS of the &lt;br&gt;
composite signal with a bit of integration and the use of &lt;br&gt;
the RMS defintion.&lt;br&gt;
&lt;br&gt;
The FFT routine identifies the equivalent power at the &lt;br&gt;
discrete frequencies with the Matlab FFT algorithm.  I am &lt;br&gt;
plotting the frequency vs. the FFT * the conjugate of the &lt;br&gt;
FFT to obtain the power signal.  For the n point data &lt;br&gt;
acquisition, I am doing the following to obtain the power:&lt;br&gt;
&lt;br&gt;
Y = fft(v,n);&lt;br&gt;
&lt;br&gt;
Pyy = Y.*conj(Y)/n ;&lt;br&gt;
&lt;br&gt;
Does someone out there know how to extract the equivalent &lt;br&gt;
RMS components of the other frequency content?&lt;br&gt;
&lt;br&gt;
best regards&lt;br&gt;
&lt;br&gt;
J. Costello&lt;br&gt;
&lt;br&gt;
&lt;br&gt;
</description>
    </item>
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