Mark,
On 12/26/2012 06:24 PM, Mark Spencer wrote:
Tom, Magnus, Ulrich:
Thanks for the comments and suggestions. They are appreciated and I
now have an even better understanding of why ADEV measurements are
not a good tool for characterizing the performance of oscillators that
are subject to transient events or glitches.
Good. You do get a gold star for your ADEV over time analysis, also
known as dynamic ADEV. It helps to see where in time a certain ADEV
wrinkle occurred so the time-plot makes sense. Trouble is, you already
have to have a clue to get to that point.
Just to clarify a few points and ask a few questions:
My concern about not putting much emphasis on Adev data for Tau's of
less than 80 seconds in the plots I’ve provided is driven by a
belief that at shorter Tau's these ADEV plots are largely showing the
noise of the counter (an HP5370B) vs the noise of the device being
measured. Perhaps the 80 second cut off point is overly conservative
but at some point I believe the counter noise will swamp the noise
from the devices being measured.
I agree with you, but rather than not showing it, show it and point out
that this is counter-noise. Then that little slope remaining has a
natural explanation and you also get a good line to follow down and
understand where the DUT noise takes over.
It would be cool if we could artificially "remove" that limitation and
see the added noise only.
AVAR_lim(tau) = (ADEV_lim(tau0)/tau)^2
ADEV_corr(tau) = sqrt(AVAR(tau)-AVAR_lim(tau))
It should be fairly simple to fit ADEV_limit to the curve, and it will
represent the white phase noise limit. Seeing that number should also
help to see where trigger noise etc. could be improved.
In a similar sense could other noise-forms be removed, so that you would
have a residual ADEV plot. This is after all what ADEV was developed
for, to establish the levels of noises and have them in separated form.
My goal was not to try and use ADEV measurements to characterize
the performance of the GPSDO in question while it was subject to
fluctuations in air flow (or subject to other transient events..)
I did include a frequency plot in my post that provides some
insight as to what happened when air flow was added.
The goal was to see if operating the GPSDO in question with air
flow changed the ADEV readings vs operating the GPSDO without air
flow. I agree ADEV may not be the best tool for this but it is easy
to collect and I have prior data to compare the results to. ADEV
also seems to be a commonly used figure of merit for characterizing
devices such as GPSDO’s.(I realize there are also other commonly
used figures of merit.)
It all comes down to how "quiet" your ambient air is to your GPSDO/OCXO.
Forced air-flow improves the thermal connectivity between the ambient
air and the GPSDO/OCXO. For many professional buildings and computer
halls, the AC/heating system is not as quiet as you would like. I've
killed several good measurement runs of free-running oscillators just by
walking up to the lab-bench and with it a wall of colder air sweeps over
it...
That's why I try to measure things in a cardboard box just to get
somewhat less airflows on the oscillators, and it works very well.
Forced air as such poses some issues, but ambient air is in my
experience the real killer.
The lowest ADEV reading I have ever observed for the GPSDO in
question came from analyzing a data set collected 45 thru 65 minutes
after air flow was applied to that GPSDO in that particular
circumstance. I found that result surprising although I agree the
absolute difference in the ADEV figures is very small.
Which I could very well believe.
It's my understanding (based largely on comments I've read on this
list over the years) that if you have roughly nx10 data points you
can begin to draw inferences from ADEV plots for Taus<n. Is this
a reasonable practice and or are there caveats one needs to be
aware of ?
Having spent many times watching the data coming into timelab, seeing
the high end flap like a whip until it settles down, I'd say that x10 is
still very unstable, but by all means look at it. The reason you want to
see real confidence intervals on your measure is to know where about the
real value could be compared to the value you currently see.
How tight you want your confidence interval to be depends on what form
of conclusion you want to take. I'd say that even more conservative
values like 100 time samples could be viewed as incorrect for some
applications. This is where you need to decide what you need. Sit down
and see the curve vary for a tau until it settles, that way you learn
where your confidence in values lie.
I agree that one test of this nature is in sufficient to draw any
firm conclusions from and much more data is needed.
It's more about building experience of what matters.
Temperature changes rather than temperature as such affects you, as long
as the oven is operating in linear state.
For one oven I once saw an interesting case, and I realized that the
oven took a "nap" to cool down and then started heating up again. In
effect, during the nap, the crystal was cooling down in an unregulated
environment, and then it was being heated up by a jolt of energy.
Another oven had a self-oscillation in the oven controller, which was
visible from power-on. It also had my current digits flopping around and
current measurement gave the controller away finally. That design was
built on a ceramic brick rather than FR4 board, so it lacked the thermal
mass to remain stable. When the vendor understood the issue, they kept
that design running arguing that the other customers didn't complain. Ah
well.
Cheers,
Magnus
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