Major_Tom wrote:Interesting.
You are doing a simple calculation for average acceleration.
What is really needed is to just an accurate hand-made (computer made) plot of x(t). You shouldn't even bother fitting the data to a function until you have an accurate physical plot of x(t).
The aim would be to to use it to plot a(t). It is the acceleration which contains the interesting info. Not just the average acceleration over some time interval but the actual instantaneous acceleration a(t) at any moment.
If you actually find peak acceleration moments exceeding gravity you've found something very big.
Calculating average acceleration will water down the peak acceleration. What the peak is and when it happened is the best data we could have.
True, one aim is to have a(t), but it's more elusive than it appears. It's very easy to state the total duration and average acceleration which actually are quite useful, everything else is an eventual necessity but a drudge and not terribly accurate when it comes to peaks.
einsteen has provided a nice plot of x(t) above but not based on numbers. I personally take this as a clever euphemism for
"I don't wan't to do this, at least not right now, would someone else like to?"
Once you have numbers for x(t), trivial calculations of first and second differences give v(t) and a(t). Going from picture to numbers is not that big of a problem for many targets. einsteen, Dr. G and I have all done data extraction in a number of ways, but all have the potential to introduce a variety of errors and none lend themselves immediately to high resolution interpretations of acceleration (can't speak to the Dr's results on that). Typically a fair bit of overhead is associated with any but the most rudimentary digitizations (i.e., the better the quality, the more time on the hands that's required).
My preference is to get data via software implementation as it is per-frame, sub-pixel (sometimes) accuracy and (almost) completely objective. In the best of cases taking data straight from an original DVD the raw data can still be pretty noisy, depending on the target. Calculating acceleration discretely per-frame then leads to some pretty wild oscillatory behavior in acceleration. I've taken some really smooth and accurate position data only to find peak accelerations of +/-25g!!!
Time-averaging is quick and helpful but not a fix. If ~30fps data is taken from a sharp and steady original and there are minimal sources of real noise (smoke, thermal, etc) then a 3 - 6 frame resampling interval for the position data would probably be reaonable and give smooth, accurate plots of position versus time.
In pixels and seconds.
Assuming the scene geometry is known with precision, x(t) in meters can be calculated and used to immediately obtain v and a, except I can almost guarantee you acceleration will still be lumpy after a such a resample. The bottom line is x(t) must be processed in some high level manner first, whether it be a curve fit or something more elaborate like DBB's Bayesian methods, then a(t) would be meaningful. *
For me, the simplest path to pixels(time) is manually via an SVG editor but I don't care for the results, they are far too subjective to claim much accuracy. Get a thousand people to make the same measurement, though, and it might be the best curve you'll ever get. David Chandler uses the Physics Toolkit, I'm not sure what einsteen uses these days, there are many, many ways. Doesn't matter to me, anything other than machine vision and full post-processing is too flawed to get a good a(t). Now, some of us have participated in doing this before, but there's nothing like the first time so the motivation to take the step from total duration to a(t) will be a little slower coming maybe.
Unless you want to do it? <wink>
*although any real transients will be obliterated by the process