kopia lustrzana https://github.com/kosme/arduinoFFT
80 wiersze
2.7 KiB
C++
80 wiersze
2.7 KiB
C++
/*
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Example of use of the FFT libray to compute FFT for a signal sampled through the ADC.
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Copyright (C) 2018 Enrique Condés and Ragnar Ranøyen Homb
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#include "arduinoFFT.h"
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arduinoFFT FFT = arduinoFFT(); /* Create FFT object */
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/*
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These values can be changed in order to evaluate the functions
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*/
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#define CHANNEL A0
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const uint16_t SAMPLES = 64; //This value MUST ALWAYS be a power of 2
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const double samplingFrequency = 100; //Hz, must be less than 10000 due to ADC
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unsigned int sampling_period_us;
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unsigned long microseconds;
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/*
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These are the input and output vectors
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Input vectors receive computed results from FFT
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*/
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double vReal[samples];
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double vImag[samples];
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void setup()
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{
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sampling_period_us = round(1000000*(1.0/SAMPLING_FREQUENCY));
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Serial.begin(115200);
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Serial.println("Ready");
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}
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void loop()
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{
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/*SAMPLING*/
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for(int i=0; i<SAMPLES; i++)
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{
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microseconds = micros(); //Overflows after around 70 minutes!
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vReal[i] = analogRead(CHANNEL);
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vImag[i] = 0;
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while(micros() < (microseconds + sampling_period_us)){
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//empty loop
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}
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}
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/* Print the results of the sampling according to time */
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Serial.println("Data:");
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FFT.PrintSignal(vReal, samples, samplingFrequency);
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FFT.Windowing(vReal, samples, FFT_WIN_TYP_HAMMING, FFT_FORWARD); /* Weigh data */
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Serial.println("Weighed data:");
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FFT.PrintSignal(vReal, samples, samplingFrequency);
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FFT.Compute(vReal, vImag, samples, FFT_FORWARD); /* Compute FFT */
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Serial.println("Computed Real values:");
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FFT.PrintVector(vReal, samples, samplingFrequency);
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Serial.println("Computed Imaginary values:");
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FFT.PrintVector(vImag, samples, samplingFrequency);
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FFT.ComplexToMagnitude(vReal, vImag, samples); /* Compute magnitudes */
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Serial.println("Computed magnitudes:");
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FFT.PrintSpectrum(vReal, samples, samplingFrequency);
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double x = FFT.MajorPeak(vReal, samples, samplingFrequency);
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Serial.println(x, 6); //Print out what frequency is the most dominant.
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while(1); /* Run Once */
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// delay(2000); /* Repeat after delay */
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}
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