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App name
Sound Spectrum Analysis
Description
The application is designed for analysis of a sound spectrum in real time (with a microphone). Besides, the application can be used as a measuring instrument of noise level (not for exact measurements). • Sound wave. • Fast fourier transform (FFT). FFT size: 2048 (the accuracy of determining the frequency of ±12 Hz), 4096 (±6 Hz), 8192 (±3 Hz), 16384 (±2 Hz), 32768 (±1 Hz), 65536 (±0.5 Hz), 131072 (±0.2 Hz). • Linear and logarithmic frequency scale. • Linear frequency scale with maximum details (there is a choice for the displayed frequency range). • Linear and logarithmic amplitude scale. • Octave bands (1/1, 1/3, 1/6, 1/12). • Window functions (Blackman, Hamming, Hann (Hanning), Blackman–Nuttall, Sine window). • A- and C-Weightings. • Peak hold. • Peak frequency detection. • Values of any point (for linear frequency scale, octave bands and sound wave (at maximum detail)). • Sound level meter (dB SPL). You can calibrate your microphone by launching a signal generator with a sinusoid frequency of 1000 Hz on another device and making the volume very low. When the sound is almost inaudible, it is necessary to find the amplitude for the frequency of 1000 Hz on the spectrum (FFT size: 16384). This value should be multiplied by 1.2 (to compensate for spectral leakage). It will be the reference value for your microphone. ESTIMATE THE TOTAL NOISE LEVEL BY USING THE SOUND WAVE MODE AT THE MAXIMUM VALUE. • Sample rate: 48000 Hz. • Taking a screenshot by lightly touching the screen. • Export data to a WAV or text file ("Y=[y1 y2... yn]", "y1;y2;... yn", "x1;y1\nx2;y2;..."). Number of points is adjusted via "FFT size". • Automatic stop in the sound wave mode (when increasing or decreasing signal strength). • Test wave.
Needs Better Callibration
by wgr17 on 2019/11/17 15:57
This app consistently responded to tones of known frequency with a peak that was at least an octave lower than the input tone.
Needs Better Callibration
by wgr17 on 2019/11/17 15:57
This app consistently responded to tones of known frequency with a peak that was at least an octave lower than the input tone.