Procedure for SPECTRUM ANALYSIS of FFT coefficients???

[Holger]

Dear all,

I need to do a FFT on an array of 20k real values. Origin of the sampled
data is a sinus wave with light harmonics.
The goal is an frequency spectrum with the magnitudes of the first 50.
harmonics.

I addressed python like:

test_arr = src_data_dict[ channel ][0:19599]
target_data_dict[ channel ] = FFT.fft(test_arr,n=50,axis=-1)

This results in an array of complex values but with unexpected big
coefficients...
(much higher than the original signal magnitudes)
How do I get the absolute magnitudes of the harmonics, which are much
lower than the
resulting absolute values of the coefficients?

The result should be like this:

1.harmonic (50 Hz) 1,0
2.harmonic (100 Hz) 0,01
3.harmonic (100 Hz) 0,08
4.harmonic (100 Hz) 0,0035
etc.


at the moment I get a resulting array like:

CH1
(1729.80103418+0j)
(366.689810532+19.5196963754j)
(370.688444025+32.162562652j)
(372.122246668+46.9545880507j)
(379.273599053+59.0724599622j)
(369.889589421+75.9247281559j)
(381.070551892+99.07345873j)
(378.800462354+106.761629308j)
(375.014128346+131.34177586j)
(389.110601354+149.320740829j)
(389.23247472+158.909042086j)
(398.875237165+197.86980788j)
(397.927158223+196.858459101j)
(402.455325066+234.651276425j)
(411.599088579+256.32156894j)
(414.469935576+254.512014918j)
(417.198515262+291.400509132j)
(426.745545674+320.769421334j)
(433.987466212+321.929780157j)
(446.124386798+350.810581686j)
(455.876025379+383.099789898j)
(458.083277747+405.592129477j)
(470.908512117+433.929598454j)
(482.083855098+468.256188814j)

What does it mean to me? How do I get to the wanted frequenca spectrum???
...

btw The maximum magnitudes of the original data are app. 70 peak

Thanks in advance for your help!!!

Regards Holger

 

[Dana DeLouis]

This results in an array of complex values but with unexpected big
Hi. There are a few different equations for a FFt. Are you able to tell
your program which one to use?
My best guess is the default equation is the same as Excel's. (Equation is
that most often used in the field of Signal Processing)
If you can't, then my best guess is that you need to divide each output by
the sample size to do your Analysis.

Magnitude is usually the Absolute value of the Complex number (ie
Sqrt(a^2+b^2).
In Excel, if A1 had:
=COMPLEX(366.689810532,19.5196963754)

Then the Magnitude is:
=IMABS(A1)
0r
367.208981

Therefore, using Excel:

=IMABS(IMDIV(A1,20000))
or
0.018

--
HTH :>)
Dana DeLouis
Windows XP & Office 2003

i had the same issue doing an FFT in DADISP. I would get a bunch of
imaginary numbers. They would graph correcty, so I had to grab the
Xvalues
and the Magnitudes off the the graph.

I am lost at converting from imaginary to Freq and Magnitude. It may be
worth looking into some of the analysis packs built into Excel.

good luck.

Dear all,

I need to do a FFT on an array of 20k real values. Origin of the sampled
data is a sinus wave with light harmonics.
The goal is an frequency spectrum with the magnitudes of the first 50.
harmonics.

I addressed python like:

test_arr = src_data_dict[ channel ][0:19599]
target_data_dict[ channel ] = FFT.fft(test_arr,n=50,axis=-1)

This results in an array of complex values but with unexpected big
coefficients...
(much higher than the original signal magnitudes)
How do I get the absolute magnitudes of the harmonics, which are much
lower than the
resulting absolute values of the coefficients?

The result should be like this:

1.harmonic (50 Hz) 1,0
2.harmonic (100 Hz) 0,01
3.harmonic (100 Hz) 0,08
4.harmonic (100 Hz) 0,0035
etc.


at the moment I get a resulting array like:

CH1
(1729.80103418+0j)
(366.689810532+19.5196963754j)
(370.688444025+32.162562652j)
(372.122246668+46.9545880507j)
(379.273599053+59.0724599622j)
(369.889589421+75.9247281559j)
(381.070551892+99.07345873j)
(378.800462354+106.761629308j)
(375.014128346+131.34177586j)
(389.110601354+149.320740829j)
(389.23247472+158.909042086j)
(398.875237165+197.86980788j)
(397.927158223+196.858459101j)
(402.455325066+234.651276425j)
(411.599088579+256.32156894j)
(414.469935576+254.512014918j)
(417.198515262+291.400509132j)
(426.745545674+320.769421334j)
(433.987466212+321.929780157j)
(446.124386798+350.810581686j)
(455.876025379+383.099789898j)
(458.083277747+405.592129477j)
(470.908512117+433.929598454j)
(482.083855098+468.256188814j)

What does it mean to me? How do I get to the wanted frequenca spectrum???
...

btw The maximum magnitudes of the original data are app. 70 peak

Thanks in advance for your help!!!

Regards Holger