Author Topic: Ultra Precision Reference LTZ1000  (Read 962992 times)

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Offline branadic

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Re: Ultra Precision Reference LTZ1000
« Reply #3000 on: June 20, 2020, 06:22:01 pm »
Quote
What kinds of issues were identified as root causes?  I will guess that EMI is/was a factor.

Turned out to be a simple issue with one button in the wrong place. Guard button on K3458A was in "low" position and not in "open". Guard of the cable was connected to case of the reference and Guard jack of K3458A, but on GND on K2002. This created a Guard loop, which created the differences.
I was able to recreate this problem today. Having multiple meters in parallel can then influence the readings.

-branadic-
« Last Edit: June 20, 2020, 09:30:04 pm by branadic »
Metrology Meeting 2020 is canceled. Looking forward for MM2021
 
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Offline SilverSolder

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Re: Ultra Precision Reference LTZ1000
« Reply #3001 on: June 20, 2020, 06:42:37 pm »

A "Guard Loop" - there's a new one! :D
 

Offline Dr. Frank

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Re: Ultra Precision Reference LTZ1000
« Reply #3002 on: June 20, 2020, 07:31:33 pm »

What kinds of issues were identified as root causes?  I will guess that EMI is/was a factor.

The 2nd definite effect were two 3458A in parallel. They were not triggered synchronously, therefore the charge injection of one would every time influence the readings of the other, and vice versa.

The StD value was extremely high, in the µV range, instead of 150..250nV, as usual.
Shows, that StD can be used as a sanity check, provided you have comparable or identical situation.
Frank
 

Offline SilverSolder

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Re: Ultra Precision Reference LTZ1000
« Reply #3003 on: June 20, 2020, 07:53:02 pm »

What kinds of issues were identified as root causes?  I will guess that EMI is/was a factor.

The 2nd definite effect were two 3458A in parallel. They were not triggered synchronously, therefore the charge injection of one would every time influence the readings of the other, and vice versa.

The StD value was extremely high, in the µV range, instead of 150..250nV, as usual.
Shows, that StD can be used as a sanity check, provided you have comparable or identical situation.
Frank

Interesting.  I have tried 4DMM in parallel but they were all triggered in sync via GPIB, that might be why I didn't see any particular problems with that method.
 

Offline niner_007

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Re: Ultra Precision Reference LTZ1000
« Reply #3004 on: June 21, 2020, 01:08:35 am »
Over 1 hr of data, 2.0189uVpp, 394nV std
 

Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3005 on: June 21, 2020, 03:46:57 pm »

What kinds of issues were identified as root causes?  I will guess that EMI is/was a factor.

The 2nd definite effect were two 3458A in parallel. They were not triggered synchronously, therefore the charge injection of one would every time influence the readings of the other, and vice versa.

The StD value was extremely high, in the µV range, instead of 150..250nV, as usual.
Shows, that StD can be used as a sanity check, provided you have comparable or identical situation.
Frank

Std. Dev. of 1 µV would mean ~6µVpp. If you further assume 6nApp from the 3458A that would lead to an output impedance of 1k.

I think the GUARD loop is much more likely to explain the high std. dev.
« Last Edit: June 21, 2020, 03:50:02 pm by e61_phil »
 

Offline niner_007

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Re: Ultra Precision Reference LTZ1000
« Reply #3006 on: June 21, 2020, 08:44:47 pm »
How do you synchronize multiple 3458A in parallel, that’s not possible is it? Why not scan the inputs with a scanner? What’s paralleling giving you? nV scanner are available, relays with low EMF are also available or can be constructed
 

Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3007 on: June 21, 2020, 08:55:21 pm »
How do you synchronize multiple 3458A in parallel, that’s not possible is it?

External Trigger, GPIB GET (That's what I'm using most of the time)


Why not scan the inputs with a scanner? What’s paralleling giving you? nV scanner are available, relays with low EMF are also available or can be constructed

Sometimes you want to compare if some disturbance was caused by the DMM or the source. And in these cases you want to integrate over the exact same point in time. INL comparisions are such an example.

Reasonable scanners are also not available to everyone.
« Last Edit: June 21, 2020, 08:56:53 pm by e61_phil »
 
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Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3008 on: June 21, 2020, 09:32:31 pm »
The conversion depends on the actual noise waveform, that's  missing in this video also.
If you have sinusoidal noise, instead of that Gaussian noise, then the rms value would be: Upp/(2*SQRT(2)).

Sorry, for beeing that late with my comment. But this is a fundamental topic and worth to discuss it deeper, I think.

In the video, they're talking about noise which creates a bell curve in the histogram and that is it what matters. The distribution is important not the signal over time. If you take all the values of your sinewave and mix the order of the values it will result in the same RMS value. Therefore, it doesn't make sense to talk about sinusoidal noise. It is more important how the shape of the histogram looks like.

The histogram of a sinewave might make sense as a worst case, because the highest abundance is at the maxima (makes absolute sense if have a look at the derivative), but that is a very unlikely shape for noise.


The 1/f (pink) noise means that there isn't only uncorrelated noise (white), but also some correlated noise. Which means the values you measure are dependend from the past (finite correlation length).

It is also wrong to say, that a gaussian histogram indicates white noise. The histogram is just the probaility density function and 1/f has also a bell shape.


@Frank: I'm absolutely sure that everything from that is known by you, I just want to make it more clear, that the signal over time is less important than the appearing values.


Edit: The standard formula for the standard deviation will give also the correct numbers, if you feed in a sinewave. There is no need to differentiate here.
« Last Edit: June 21, 2020, 09:48:41 pm by e61_phil »
 

Offline Kleinstein

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Re: Ultra Precision Reference LTZ1000
« Reply #3009 on: June 22, 2020, 07:14:36 pm »

The 1/f (pink) noise means that there isn't only uncorrelated noise (white), but also some correlated noise. Which means the values you measure are dependend from the past (finite correlation length).

It is also wrong to say, that a gaussian histogram indicates white noise. The histogram is just the probaility density function and 1/f has also a bell shape.
With 1/f noise it depends on the details. One may have a bell shaped histogram, but the histogram can also look quite different (e.g. with dominant popcorn noise - which also gives an approximately 1/f spectrum). If the 1/f part is more like some random walk the measured histogram may also look different from the gauss bell curve. It is possible to a bell shaped histogram with 1/f noise, but this is not always the case.

The histogram and frequency spectrum are kind of complementary. So one would need to look at both - there is no way to convert one to the other.
 
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Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3010 on: June 25, 2020, 10:24:26 am »
I played with some simulated random walks. To evaluate "how wrong" 6x the standard deviation compared to the "real" peak to peak value is, I created 1000 random walks. Every walk was a million steps long. I calculated the standard deviation and the peak to peak value for every walk and compared them.

The mean ratio of 6x std. dev / pp was 1.38 (+/- 0.19). Which means you will almost ever overestimate the peak to peak value by taking 6x the standard deviation in the case of a random walk.

Btw.: The standard error of the standard deviation is S/sqrt(2(n-1)) which means you will already have 0.18 sigma (relative to a standard deviation of 1) if you only take 16 measurments with your 3458A.
« Last Edit: June 25, 2020, 03:41:51 pm by e61_phil »
 
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Online dietert1

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Re: Ultra Precision Reference LTZ1000
« Reply #3011 on: June 25, 2020, 02:17:44 pm »
What happens to the stdev/pp ratio for real (shorter) measurement series?

For example in my current observation of two LTFLU 10 V references i see a stdev = 0,029 ppm of the daily averages, so times 6 gives an expected pp of 0,174 ppm. After 38 days i have an observed pp of 0,11 ppm (minimum -0,065 ppm, maximum 0,046 ppm). So that gives a ratio of about 1.6 (overestimation of pp by 6x formula). In this case the factor seems to be more like 4 instead of 6.

Maybe this case is not a random walk, but something else. Maybe air pressure changes.

Regards, Dieter
 

Offline Kleinstein

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Re: Ultra Precision Reference LTZ1000
« Reply #3012 on: June 25, 2020, 03:27:11 pm »
Popcorn noise can give a rather low ratio for peak to peak values relative to RMS value.
Some periodic background (e.g. day / night temperature or pressure variations could also give a small ratio).
 

Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3013 on: June 25, 2020, 03:37:45 pm »
What happens to the stdev/pp ratio for real (shorter) measurement series?

For example in my current observation of two LTFLU 10 V references i see a stdev = 0,029 ppm of the daily averages, so times 6 gives an expected pp of 0,174 ppm. After 38 days i have an observed pp of 0,11 ppm (minimum -0,065 ppm, maximum 0,046 ppm). So that gives a ratio of about 1.6 (overestimation of pp by 6x formula). In this case the factor seems to be more like 4 instead of 6.

Maybe this case is not a random walk, but something else. Maybe air pressure changes.

Regards, Dieter

Maybe it was a bit misleading to say "Seems to me, that there is no need to take values lower than 6 to estimate the pp noise" (Therefore, I deleted that sentence in the post above). What I wanted to say was: 6 is already conservative. It is most likely less than 6x std. dev. (6 / 1.38 = 4.34)
« Last Edit: June 25, 2020, 03:42:29 pm by e61_phil »
 

Offline mrflibble

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Re: Ultra Precision Reference LTZ1000
« Reply #3014 on: June 25, 2020, 03:52:56 pm »
I played with some simulated random walks. To evaluate "how wrong" 6x the standard deviation compared to the "real" peak to peak value is, I created 1000 random walks. Every walk was a million steps long. I calculated the standard deviation and the peak to peak value for every walk and compared them.

Quick note regarding peak-to-peak value of a simulated random walk.
You may also want to try:
- do random walk of N steps, storing each location x[n] at step number n.
- sort all x[n]
- for maximum, take sorted list entry at index floor(0.95*N)
- for minimum, take sorted list entry at index floor(0.05*N)

Notation: x[n]is location at step number n, assuming start position x[0]=0.
Adjust the (0.05, 0.95) constants to taste.

Similar story for the mean value. Since you sorted that list already, you might as well take the median, so x[ floor(N/2) ].

PS: request from those of us who do find this sort of thing interesting, but are a but strapped for time... I did not read the entire thread today, so I'm sorry if I missed the context that would have made it obvious... But: for walk_example_1 and walk_example_2, I couldn't get the information of what it was. I.e, is this a single trial of N=1E6 steps. (yes). Or is this the sum of all M=1E3 trial runs. (No). To be sure it was a single trial the image filenames actually were more informative. That  and eyeballing the number of bins ~ 50. And eyeballing the area of the histograms .... "mmmh, if I put this blob here and that blob there I get an about level line around the count of ... 20000. Okay. About 50 * about 20000 equals about 1E6. Check, it is a single trial. Or you could just put that information in the plot title. Just a suggestion. I am as guilty of forgetting to do this as the next person. Reason I started doing proper annotation, titles and whatnot even in my own projects that never see the light of day: yeeeaaaars from now my future self will thank my current self for making it easy to follow what the hell I was doing at the time. ;)

Oh yeah, random other note: (PPS? :P ) If you want to solve for the expectation value of the (min,max) values of a random walk you can use the infinity-norm of the x-vector, where again x[0] is start, and X[N] is end position. So in this case x is an (N+1) dimensional vector. max(x) == inf-norm(x). Using that you can solve for min,max analytically. Or do it the proper aka lazy way and just solve for max, then do some handwaving and claim symmetry relation between min & max.

Something similar can be done for the (0.05*N, 0.95*N) values, but that might get too involved for a quick experiment. If interested, lookup "order statistics".

Related linkies:
https://en.wikipedia.org/wiki/Norm_(mathematics)#Maximum_norm_(special_case_of:_infinity_norm,_uniform_norm,_or_supremum_norm)
https://en.wikipedia.org/wiki/Order_statistic
 
 
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Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3015 on: June 25, 2020, 04:01:49 pm »
@mrflibble: Thanks for the hints. I already played with the sorted "path" to estimate only 99.73% (6 sigma) for peak to peak. But the difference is so small that I didn't cover it in the first post. 95% would only be equal to 2 sigma -> factor 4 instead of 6.

You're absolutely right with the shown examples. I promise to make better titles in the future ;)
« Last Edit: June 25, 2020, 09:05:50 pm by e61_phil »
 
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Online dietert1

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Re: Ultra Precision Reference LTZ1000
« Reply #3016 on: June 27, 2020, 05:37:55 pm »
When i was thinking about my data and about this difference between peak-to-peak expected from single point standard deviation and observed peak-to-peak values, maybe this is caused by looking at the difference of two reference voltages.

I guess the rare peak values of one reference will "collide" with the rare peak values of opposite polarity of the other reference even more rarely. So one would see 1.4 * the RMS of one reference but only 1 * the peak-to-peak values of one reference. Such a model could explain my observation until now. Maybe the expected higher peaks will appear after taking a very long data series with hundreds of points.
In other low noise tests where one device (meter) is much better than the other (DUT), the proposed factor 6 should hold better.

Regards, Dieter
 

Online e61_phil

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Re: Ultra Precision Reference LTZ1000
« Reply #3017 on: June 27, 2020, 06:54:26 pm »
Hi Dieter,

I'm not sure if you had that in mind, but I think your example is something like two normal distributions (one for every reference) which have similiar properties. Therefore, I made two distributions with the same µ and sigma (0 and 1). It seems to me, that the ratio between peak to peak and the standard deviation hasn't changed. (And I think that was expected because of the central limit theorem)

Best regards
Philipp
 

Online dietert1

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Re: Ultra Precision Reference LTZ1000
« Reply #3018 on: June 27, 2020, 08:53:38 pm »
Yes, that's what is expected, except i was wondering how long it will take to observe those peaks. And somehow i think it should depend on bandwidth. I could try what i get when looking at 24 * 38 hourly averages instead of 38 daily averages.
Maybe i should just be patient and wait for the first 2000 hours as everybody else.

Regards, Dieter
 


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