Campbell Scientific CR9000X Measurement and Control System - Manual (Page 198)

Section 6. Data Table Declarations and Output Processing Instructions
FFT (Source, DataType, N, Tau, Units, Option)
The FFT function performs a Fast Fourier Transform on a time series of
measurements stored in an array. It can also perform an inverse FFT,
generating a time series from the results of an FFT. Depending on the output
option chosen, the output can be: 0) The real and imaginary parts of the FFT;
1) Amplitude spectrum. 2) Amplitude and Phase Spectrum; 3) Power
Spectrum; 4) Power Spectral Density (PSD); or 5) Inverse FFT.
Parameter
& Data Type Enter FFT PARAMETERS
Source
Variable
The name of the Variable array that contains the input data for the FFT.
DataType A code to select the data storage format. Read More: See Section 4.2.4.4 Data Types
Constant Alpha Code Numeric Code Data Format
IEEE4 24 IEEE 4 byte floating point
FP2 7 Campbell Scientific 2 byte floating point
UINT2 21 2 Byte unsigned integer
Long 20 4 Byte Integer value
N
Constant
Number of points in the original time series. The number of points must be a power of 2 (i.e., 512, 1024,
2048, etc.).
Tau
Constant
The sampling interval of the time series.
Units The units for Tau.
Constant Alpha
Code Numeric
Code
Units
USEC 0 Microseconds
MSEC 1 Milliseconds
SEC 2 Seconds
MIN 3 Minutes
Options to indicate what values to calculate and output.
Constant Code Result
0
1
2
3
4
5
FFT. The output is (N/2)+1 complex data points, i.e., the real and imaginary parts of the
FFT. The first pair is the DC pair; the last pair is the Nyquist pair. Zero is seen for the DC
and Nyquist imaginary components.
Amplitude spectrum. The output is N/2+1 magnitudes. With Acos(wt); A is magnitude.
Amplitude and Phase Spectrum. The output is N/2+1 pairs of magnitude and phase; with
Acos(wt -
φ); A is amplitude, φ is phase (-π,π). The first pair is the DC pair; the last pair is
the Nyquist pair. Pi is seen for their imaginary component.
Power Spectrum. The output is (N/2)+1 values normalized to give a power spectrum.
With Acos(wt -
φ), the power is A 2 / 2. The summation of the N/2 values yields the total
power in the time series signal.
Power Spectral Density (PSD). The output is (N/2)+1 values normalized to give a power
spectral density (power per herz). The Power Spectrum multiplied by T = N*tau yields the
PSD. The integral of the PSD over a given bandwidth yields the total power in that band.
Note that the bandwidth of each value is 1/T Hertz.
Inverse FFT. The input is (N/2)+1 complex numbers, organized as in the output of option
0, which is assumed to be the transform of some real time series. The output is the time
series whose FFT would result in the input array.
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