> Indeed, ADEV is for random freq variation not easily measured by other means.
Well, no, ADEV is the two-sample deviation of fractional frequency differences over time. That's really all you can say about it. There's not really any such thing as "true ADEV" -- a measurement either meets the mathematical criteria for Allan deviation, or it doesn't. > Temperature fluctuations do not cause random freq changes and the > temperature's effect should be removed if one wants accurate long term > ADEV numbers. No, accurate ADEV numbers are whatever you see on an accurate ADEV plot. :) If I measure two sources in the same environment and I see HVAC ripple on one ADEV trace but not on the other, then that may be useful information, or even the only information I care about. (Of course, it's only useful if the bin density is high enough to show the effect in question, but that's not the fault of the ADEV metric itself.) If you don't want to observe the effect of temperature fluctuations on your DUT, random or otherwise, the correct solution is not to use a different metric or to tweak the data, but to shield the DUT against the temperature variations in question. > Even daily diurnal cycles due to temperature can have major negative effect > on ADEV numbers as low as 2000 to 3000 seconds, Your bin density may be insufficient in that case. ADEV is not unlike an FFT in that regard -- the denser the bins, the higher the resolution, subject to limitations imposed by the window transfer function. (Enrico Rubiola has suggested that we should have been using FFT-like measures for long term stability all along, instead of ADEV.) It's true that the ADEV function is not all that sharp, but you shouldn't ordinarily see effects removed from their causes by a 40:1 tau ratio. IMHO, if you are seeing significant degradation at the 2000-second level caused by diurnal cycles at the 12-hour level, something may be wrong. Outliers are another matter, due to the infinite "ringing" that a step function causes. They should be removed from ADEV and considered as a separate source of error. Transients cause some pretty horrible effects in FFTs as well, regardless of the window characteristics. Offhand, I can't think of any simple frequency-stability metrics that are good at ignoring outliers, and I'm not sure it'd be a good thing if we were to invent one. > and if there is an Heater or AC cycling, then any ADEV numbers about a few > hundred seconds can be due to TempCoeff, which should not be measured > with ADEV or included in ADEV plots. Again, fractional frequency differences are fractional frequency differences. ADEV will show temperature effects, as will an FFT or most other metrics worth using. If you don't want to see these effects, you need to take the appropriate measures to fix the environment, the DUT, the instrumentation, or all of the above. > This is much the same as a single outlier data point that can screw up the > whole ADEV plot and make it pretty much meaningless and unrepeatable. > Ditto for linear ageing, Should be remove first if one wants true ADEV > plots. Linear drift is a good thing to take out... *if* you explicitly want to exclude it from your observation of fractional frequency-difference statistics. Maybe you consider drift or aging to be a valid part of the statistics you're collecting. If so, leave it in. Maybe you plan to discipline the DUT in a way that will remove drift and aging. If so, remove it. You're going to get a "valid" measurement of ADEV either way... but determining whether ADEV is really the best metric to use, and interpreting it in light of your application, is always up to you. -- john _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
