[time-nuts] crystal againg fit (was: Excel logarithmic function)

[Scott Stobbe]

Sadly I don't think there is a concise answer to this, in reality you would
make the decision on the fly depending on how much data you have and which
model is the most well behaved.

I think it's a really interesting topic to see some of what goes into an
OCXO, a guaranteed limit on aging is one the many things.

Part of the reason that information on the topic is somewhat is scattered,
is if a commercial application genuinely needed 1e-12 stability for 100
days free-running, the answer without hesitation would be atomic. Then as
you dial back the long-term stability requirement how much NRE are you
willing to spend; which is also why there doesn't seem to plenty of worked
examples out there.

On Thu, Nov 24, 2016 at 10:49 AM, Attila Kinali <attila at kinali.ch> wrote:

> On Thu, 24 Nov 2016 08:16:08 -0500
> Bob Camp <kb8tq at n1k.org> wrote:
>
> > If you take the bad aging (out of spec) parts out of the pile, those are
> the ones
> > with the best fit. They have very pretty curves and they stick to those
> curves
> > for a *long* time. They have a single dominant cause for their aging ( =
> the defect).
> > The rest of the parts have all of the causes bashed down by the process
> so that
> > over a 20 or 30 year span, there probably is no single dominant cause.
>
> Then the question becomes: What would be a good fitting function for
> the typical application of an OCXO that is regularly measured with
> not too long time spans (e.g. GPSDO)? From the discussion it seems
> that a second or third order Taylor would be sufficient to capture
> aging for a span of 10-100 days.
>
>                         Attila Kinali
>
> --
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