I built an audio timegrapher feature for my watch accuracy app, ChronoLog. Professional timegraphers use a piezo contact sensor and can cost upwards of $1,000. I wanted to do it with a phone mic.
The problem: an iPhone's built-in microphone picks up a mechanical watch's tick at about 1.5 dB SNR. The solution turned out to be epoch folding — the same technique radio astronomers use to find pulsars. Stack 100+ tick periods together and you get +20 dB of effective gain, enough to reliably measure rate and beat error.
The post covers the full DSP pipeline — bandpass filtering, epoch folding, autocorrelation (and why it finds harmonics before fundamentals at low SNR), Kalman filtering for convergence — and what I learned from five rounds of device testing.
Did you consider trying the iPhone accelerometer? Perhaps lay the phone face down on the table and then lay the watch on the back? Wondering if this would have higher or lower SNR.
I don't think it would work because the accelerometer updates are at too low a frequency. Apple's developer info says:
```
Before you start the delivery of accelerometer updates, specify an update frequency by assigning a value to the accelerometerUpdateInterval property. The maximum frequency at which you can request updates is hardware-dependent but is usually at least 100 Hz.
```
100Hz is way too slow. Presumably some devices go higher but according to the article the peak signal is in the 3kHz to 15kHz range.
I've tried these as apps before, and they never worked that well unfortunately. Perhaps the ticks aren't loud enough, or phone mics aren't that great, or background noise gets picked up as ticks, who knows.
I bought and use the item linked below. It's big, and feels like tech straight out of the cold war era, but works great.
I built an audio timegrapher feature for my watch accuracy app, ChronoLog. Professional timegraphers use a piezo contact sensor and can cost upwards of $1,000. I wanted to do it with a phone mic.
The problem: an iPhone's built-in microphone picks up a mechanical watch's tick at about 1.5 dB SNR. The solution turned out to be epoch folding — the same technique radio astronomers use to find pulsars. Stack 100+ tick periods together and you get +20 dB of effective gain, enough to reliably measure rate and beat error.
The post covers the full DSP pipeline — bandpass filtering, epoch folding, autocorrelation (and why it finds harmonics before fundamentals at low SNR), Kalman filtering for convergence — and what I learned from five rounds of device testing.
Did you consider trying the iPhone accelerometer? Perhaps lay the phone face down on the table and then lay the watch on the back? Wondering if this would have higher or lower SNR.
I don't think it would work because the accelerometer updates are at too low a frequency. Apple's developer info says:
``` Before you start the delivery of accelerometer updates, specify an update frequency by assigning a value to the accelerometerUpdateInterval property. The maximum frequency at which you can request updates is hardware-dependent but is usually at least 100 Hz.
```
100Hz is way too slow. Presumably some devices go higher but according to the article the peak signal is in the 3kHz to 15kHz range.
How does it compare to other apps ("watch accuracy meter" for example) on android?
I've tried these as apps before, and they never worked that well unfortunately. Perhaps the ticks aren't loud enough, or phone mics aren't that great, or background noise gets picked up as ticks, who knows.
I bought and use the item linked below. It's big, and feels like tech straight out of the cold war era, but works great.
https://www.amazon.com/gp/aw/d/B0081SSJZG