why fundamental Frequency and magnitude are not null when microphone is off? - qt

Question

I would like to make real time audio processing with Qt and display the spectrum using FFTW3.
What I've done in steps:
I capture any sound from computer device and fill it into the buffer.
I assign sound samples to double array
I compute the fundamental frequency.
when I'm display the fundamental frequency and Magnetitude when the microphone is on but no signal(silence) , the fundamental frequency is not what I expected , the code don't always return zero , sometimes the code returns 1500Hz,2000hz as frequency
and when the microphone is off (mute) the code don't return zero as fundamamental frequency but returns a number between 0 and 9000Hz. Any help woulbd be appreciated
here is my code
QByteArray *buffer;
QAudioInput *audioInput;
audioInput = new QAudioInput(format, this);
//Check the number of samples in input buffer
qint64 len = audioInput->bytesReady();
//Limit sample size
if(len > 4096)
len = 4096;
//Read sound samples from input device to buffer
qint64 l = input->read(buffer.data(), len);
int input_size= BufferSize;
int output_size = input_size; //input_size/2+1;
fftw_plan p3;
double in[output_size];
fftw_complex out[output_size];
short *outdata = (short*)m_buffer.data();// assign sample into short array
int data_size = size_t(outdata);
int data_size1 = sizeof(outdata);
int count = 0;
double w = 0;
for(int i(chanelNumber); i < output_size/2; i= i + 2) //fill array in
{
w= 0.5 * (1 - cos(2*M_PI*i/output_size)); // Hann Windows
double x = 0;
if(i < data_size){
x = outdata[i];
}
if(count < output_size){
in[count] = x;// fill Array In with sample from buffer
count++;
}
}
for(int i=count; i<output_size; i++){
in[i] = 0;
}
p3 = fftw_plan_dft_r2c_1d(output_size, in, out, FFTW_ESTIMATE);// create Plan
fftw_execute(p3);// FFT
for (int i = 0; i < (output_size/2); i++) {
long peak=0;
double Amplitudemax=0;
double r1 = out[i][0] * out[i][0];
double im1 = out[i][3] * out[i][4];
double t1 = r1 + im1;
//double t = 20*log(sqrt(t1));
double t = sqrt(t1)/(double)(output_size/2);
double f = (double)i*8000 / ((double)output_size/2);
if(Magnitude > AmplitudeMax)
{
AmplitudeMax = Magnitude;
Peak =2* i;
}
}
fftw_destroy_plan(p3);
return Peak*(static_cast<double>(8000)/output_Size);

Answer 1

What you think is silence might contain some small amount of noise. The FFT of random noise will also appear random, and thus have a random magnitude peak. But it is possible that noise might come from equipment or electronics in the environment (fans, flyback transformers, etc.), or the power supply to your ADC or mic, thus showing some frequency biases.
If the noise level is low enough, normally one checks the level of the magnitude peak, compares it against a threshold, and cuts off frequency estimation reporting below this threshold.