Experiment: Frequency History
The experiment "Frequency History" is similar to the "Audio Autocorrelation" experiment as it determines the frequency and period of a single frequency audio signal (for example a single note from a guitar - not a chord) from the microphone. By only analysing 10ms of audio as fast as possible, it aims at showing the change in frequency over time.
There are no hardware requirements. The microphone is used to measure any sound. However, depending on your requirements you might want to attach an external microphone to your device.
Also, there are some limitations to the type of audio signal that gives reasonable results. As this experiment uses an autocorrelation to calculate the frequency, it can not distinguish multiple frequency at the same time. This means, that for example a chord will give no meaningfull result. Similarly, background noise can have a rather strong impact on the reliability of the measured frequency.
There is no specific setup. Depending on what audio source you want to measure, you might want to aim the microphone at the sound source and try to damp the sound from the environment.
The analysis is very similar to the simple autocorrelation experiment: This experiment records 10ms blocks of audio and calculates the autocorrelation of the data. This gives a mathematical description of how much the data "resembles itself" (if you are interested in this, please go ahead and research "autocorrelation") as a function of a shift of the data on its time axis. Typically, the autocorrelation data has a maximum at a shift of zero as of course the data resembles itself perfectly (it is obviously an exact match). The next maximum will be found if the data is shifted by the periodicity of the original signal, because now each period of the signal has to be matched to the next period, which will work quite well for a periodical signal. In-between these maxima, the autocorrelation is lower (usually negative).
phyphox will try to find the first maximum after zero shift, which is the period of the signal and the frequency of the signal is its inverse.
10ms is very short to give a precise reading, but the idea of this experiment is to give a fast succession of readings to display their change over time.
Problems and resolutions
- The frequency is unreliable or entirely wrong. Make sure that the audio signal mostly consists of a single frequency. If there is a lot of background noise or other frequencies, this method does not give a reasonable result. You might want to try the Audio Spectrum experiment instead.