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Measuring frequency from an analog input

I'm reading in an analog signal from a DAQ. It is essentially a sine wave. I need to detect the frequency of the sine wave. Is there an easy way to just read in the data from the analog signal and calculate the freqency? The program will be running constantly when a loop is enabled to be constantly finding the frequency of this changing signal. I'll need to read in the data as long as the "run" loop is still enabled, so reading in the frequency has to be relatively fast.
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Try Extract Single Tone Information.vi. Its in the Analyze>Waveform Measurements palette.
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jdaltonnal wrote in news:5065000000080000001B250000-
993342863000@exchange.ni.com:

> I'm reading in an analog signal from a DAQ. It is essentially a sine
> wave. I need to detect the frequency of the sine wave. Is there an
> easy way to just read in the data from the analog signal and calculate
> the freqency? The program will be running constantly when a loop is
> enabled to be constantly finding the frequency of this changing
> signal. I'll need to read in the data as long as the "run" loop is
> still enabled, so reading in the frequency has to be relatively fast.

Dennis Knutson's suggestion to use the Extract Single Tone Information VI
is a good one.

Some care should be taken when performing this measurement, though, because
what you a
re doing is dynamic signal measurement. Problems can come up if
you don't sample at an adequate rate and apply appropriate front-end low-
pass filtering for anti-aliasing. Sampling should be done using buffered
acquisition (as opposed to single point, as for temperature) using a
sampling rate of at least twice the maximum frequency of interest. Low-pass
filtering should block frequencies above 1/2 your sampling rate.
Without such provisions, you'll likely see aliasing--frequencies that
aren't actually in your signal and result from sampling.

For more information, you might take a look at the National Instruments
developer's zone. Take a look at application note 41, Fundamentals of FFT-
based spectral analysis.

Hope this helps,

--Sam
Sam Shearman
Product Manager, Signal Processing and Analysis Software
National Instruments
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