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Finally got around to testing tg on a windows machine, just put the watch on the headphone microphone.
The trace looks wonky, I did get some data with my own software and that looks a bit nicer.
Could it be that those pretty big wobbles of the escapementwheel throw off the peakdetection?
My method goes as:
I get the black raw data, first thing we do is get the derivative, this highlights the sharpest noise. We take the absolute value since we are interested in the location in time of the tick (or tock).
We smooth out those orange peaks with a gaussian filter and compare the resulting green line with the average pulse shape (differs for tick or tock) in blue. To determine the shift between the two we do a crosscorrelation and find where the peak is. That is the shift.
The trace looks wonky, I did get some data with my own software and that looks a bit nicer.
Could it be that those pretty big wobbles of the escapementwheel throw off the peakdetection?
My method goes as:
I get the black raw data, first thing we do is get the derivative, this highlights the sharpest noise. We take the absolute value since we are interested in the location in time of the tick (or tock).
We smooth out those orange peaks with a gaussian filter and compare the resulting green line with the average pulse shape (differs for tick or tock) in blue. To determine the shift between the two we do a crosscorrelation and find where the peak is. That is the shift.
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