Campbell Scientific RTDAQ Software - Manual (Page 202)

Section 7. Monitoring Data in Real-time
For more information about configuring the histogram window, see the section
entitled: Configuration of FFT and Histogram windows later in this chapter.
7.8 Fast Fourier Transform Spectra
RTDAQ can display Fast Fourier Transform spectra (FFT spectra) that have
been created by the datalogger. The display will be updated as fast as new
records are received from the datalogger. This often results in a real-time
instructions must be
defined in the CRBasic program running on the datalogger to which RTDAQ is
connected. These output instructions include FFT (available for all RTDAQ
dataloggers) and FFTSample (used only on the CR9000X with at least one
CR9052 Filter Module installed).
RTDAQ does not create FFT spectra from time series
response. For this to function properly, the proper output
measurements. It only displays FFT spectra that have been
calculated and stored by the datalogger.
7.8.1 Brief Overview of Fourier Analysis
Fourier analysis takes a signal from the time domain and transforms it into the
frequency domain. The fundamental principle used with Fourier analysis is
that any time domain signal that is sampled can be represented with a group of
sinusoidal functions of varying amplitudes and phases, which are then linearly
combined to represent (or approximate) that original time domain signal. A
typical display of this frequency representation would be to show the
amplitudes of the sines and cosines at various frequencies (such as the height
of a bar representing the amplitude). An algorithm for performing these
calculations known as the Fast Fourier Transform (FFT) algorithm has come
into popular use during the last few decades due to its efficiency and favorable
computational speed. An FFT spectrum is used for analyzing the different
frequency components that comprise a measured signal. Often, by identifying
ital
uency interval.
These are known as bins. FFT spectra can be represented in scalar form (i.e.,
single-valued; one bin value per frequency range), such as Amplitude or Power
NOTE
the strongest frequency components, filtering strategies or other kinds of dig
signal processing techniques can be devised for interpreting or manipulating
measured data.
When discrete signals are provided as inputs to the algorithm, the output is also
a discrete set of values, each one having reference to a freq
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