Author Topic: Statistical arrays  (Read 13927 times)

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Online dietert1

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Re: Statistical arrays
« Reply #100 on: July 06, 2019, 09:33:58 pm »
No, Mr. Pettis, it's not April 1st today. If you present a table with limits you will stick to, that's it. We know from TiNs measurements that your resistors are no better than econistors. My econistor humidity test was to confirm what others found before. Yes, the econistor remains in it's dry pack and i will measure it again after a week or so. I think Mr. Pettis is creating a lot of noise without any signal.

I was not measuring one Nomca part but six, a total of 48 resistors. Sooner or later i will also characterize the other 34 econistors we have, looking at their TCs. And i wrote about bridge measurements were i had one 13:1 Nomca divider outside and one inside the TEC box, both running from the same 10 V reference. That was the measurement which resulted in the +/- 0,5 ppm/K limit for a 18°C cycle. So it wasn't a DVM resistance measurement only, but very close to the indended application.

Concerning resistor noise: Is there a link/reference on how those measurements were done? I mean before someone talks us into using parts with 60 ppm humidity dependence in order to avoid some 0,07 ppm extra noise, i'd like to have a closer look. Maybe a Nomca array just needs to be protected from random ventilation. I mean its thermal mass is very small in comparison to its surface.

Regards, Dieter
« Last Edit: July 08, 2019, 02:12:37 pm by dietert1 »
 
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Offline branadic

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Re: Statistical arrays
« Reply #101 on: July 08, 2019, 05:32:52 pm »
Dieter,

I'm about to measure some values soon, still preparing everything. Attached one NOMCA16035001 together with a NCP15WF104F03RC NTC on a ceramic board, configured as a 10k, with the board glued to a BPR10101J resistor as part of an oven.

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Online Kleinstein

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Re: Statistical arrays
« Reply #102 on: July 08, 2019, 05:51:52 pm »
....
Regarding recent discussion, I was curious about 1/f noise of thin films, especially NOMCA vs larger models. I did a quick test dividing LTZ1000 voltage by 2 and measuring 0.1-10Hz pp noise within 1 minute period.

LTZ1000: 0.15 ppm
noname THT 3.3k metal film: 0.16 ppm
NOMCA 10k, 3 samples tested, 6 resistors used every time: 0.22-0.25 ppm
S102K (refurbished) 11k, 6 resistors used: 0.16 ppm

Additionally, long time ago I found this publication containing 1/f noise tests of various resistor types and models. Seems like a lot of models achieve good performance with almost no 1/f noise, even in SMD 0402 size.

The link in this older post is quite good. The measurement for resistor 1/f noise is relatively easy with a bridge from 4 equal resistors, as described in the link. It mainly take a low noise amplifier, some instrument to record the data at a moderately low frequency. The MIL standard uses a slightly different setup, with only one resistor as a DUT and some fill resistor, but its a little more tricky, especially at very low noise.
So a test may be reasonably easy.

From the measurements quoted the NOMCA resistors as a 1:1 divider (3 x 10 K in parallel each) results in noise similar to the LTZ1000 noise in the 0.1 -10 Hz range  (noise power about doubles).

The < -30 dBi noise specs for the NOMCA are not really good. From the divider measurements they don't seem to be much better than specs.
For the temperature setting divider at the LTZ1000 this would still be well good enough, but not for a 7 to 10 V stage.
 

Offline Kosmic

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Re: Statistical arrays
« Reply #103 on: July 08, 2019, 06:36:12 pm »
Dieter,

I'm about to measure some values soon, still preparing everything. Attached one NOMCA16035001 together with a NCP15WF104F03RC NTC on a ceramic board, configured as a 10k, with the board glued to a BPR10101J resistor as part of an oven.

-branadic-

Nice assembly  :-+

Is it expensive to order some custom ceramic boards like that ?
 

Online dietert1

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Re: Statistical arrays
« Reply #104 on: July 09, 2019, 05:14:17 am »
Yes, this assembly will certainly perform very well. The large resistor will provide distributed heating with small gradients. But this type of work really requires some sturdyness, since it will take a long time, maybe a year or more to learn how useful such a device can be and whether it helps.
I would also like to mention again SEI RTAN resistors that could be used to do something similar, i mean make an array in a thermostat. Those parts appear to be metrology level, too.

The measurements i started on drying Nomca arrays turn out to be much more difficult than the econistors. I have not seen any humidity effect now after several days, which is good news. The temperature effects are much bigger, even with a part ("C") with only 5 ppm/K on average. I also put a 5 KOhm UPW50 resistor into the drypack and did not see a single ppm change after 24 hours. Apparently our econistors are sealed only on one end and open on the other. And their material is somehow softer, while the UPW50 package appears more like usual IC packages - extremely dense plastic.

Regards, Dieter
 

Offline branadic

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Re: Statistical arrays
« Reply #105 on: July 09, 2019, 04:16:30 pm »
Quote
Is it expensive to order some custom ceramic boards like that ?

Can't tell you that as this is a "design" I gave to my colleague to develope the process on a real world application and without the use of individual masks (digital process chain).

-branadic-
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Online dietert1

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Re: Statistical arrays
« Reply #106 on: July 21, 2019, 09:14:35 pm »
After about 2 weeks in the drypack a Nomca array exhibits a humidity effect of about 25 ppm on the resistance. Yet the division ratio of a 13:1 divider changed by only 0.7 ppm under these conditions.
After 2 weeks in the drypack, some wirewound resistors have gone mad and exhibit changes of up to 220 ppm (econistor) and about 80 ppm (UPW50). Changes of econistors differ by more than 30 ppm, so useless for metrology grade voltage dividers. Hard to believe, need to check more.

I also found that the TC compensation scheme proposed above using a certain combination of resistors is delicate. I mean the TCs i determined using a 18 °C oven cycle (using box method) are useful but may not give the best possible result at room temperature. Currently i am trying to refine temperature measurements using a PT1000 sensor close to the Nomca array in order to separate humidity effects from temperature effects.
I also suspect that self heating may affect the compensation scheme.

Regards, Dieter
 
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Offline d-smes

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Re: Statistical arrays
« Reply #107 on: July 22, 2019, 09:12:25 am »
After about 2 weeks in the drypack ...
By drypack, I assume you mean a desiccant material.  Are you just throwing a few pouches in a metal box?  Or completely encapsulating the resistors in a sealed jar or equivalent?  Any relative humidity readings?  I know with insulation systems, there is such a thing as too dry.  Wondering if that applies here.
 

Online dietert1

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Re: Statistical arrays
« Reply #108 on: July 22, 2019, 10:32:29 am »
When we got our 3D printer, we bought 4 kg of orange silica gel to make a drybox for filaments. That drybox got about 1 kg in it and the hygrometer has been reading 10 or 11 % rH ever since. That's the minimal reading of the hygrometer (some technical or physical limit). I just put some spoons of that silica gel into plastic envelopes together with the resistors. The envelopes are closed except where the cables enter. I think humidity inside has been below 11 % rH for at least 14 days.
The results are somewhat confusing. During the first 24 hours 10 KOhm, when i was watching them regularly, econistors exhibited a resistance change of about -70 ppm, but now they are about 150 ppm above the initial value. I think i will take them out of the drypack and test whether they go back to initial values or whether they have been damaged. The UPW50 is 80 ppm above initial value after 14 days.

Regards, Dieter

PS: Now i got a Sensirion SHT31 Smart Gadget Development Kit that indicates less than 5 % RH inside of the drypack (PE bag).
« Last Edit: August 07, 2019, 10:19:59 am by dietert1 »
 

Offline 3roomlab

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Re: Statistical arrays
« Reply #109 on: July 26, 2019, 07:40:49 am »
In the nomca pdf, it states the load life drift at 125C (looks like derated = 100mW?) is 290ppm. what should be the expected/calculated load life drift be at 1mW? 2.9ppm (125C)?
do you know what he is talking about? why is he so surprised?
 

Online Kleinstein

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Re: Statistical arrays
« Reply #110 on: July 26, 2019, 08:05:56 am »
For the load life it is likely the temperature that is most important So it would likely not make a difference if with current or with external heating.
 

Offline splin

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Re: Statistical arrays
« Reply #111 on: July 26, 2019, 01:33:20 pm »
In the nomca pdf, it states the load life drift at 125C (looks like derated = 100mW?) is 290ppm. what should be the expected/calculated load life drift be at 1mW? 2.9ppm (125C)?

Take a look at this Vishay technical note 'Drift Calculation for Thin Film Resistors':

https://www.vishay.com/docs/28809/driftcalculation.pdf

Note that the numbers in 2.4, ' Precision Operation Mode' don't seem to be right. Given from 2.1, drift @ 1000 hours, 125C = .25%.

Therfore at 85C it should be 0.25% / (2^((125-85)/30) = 0.1%, not < .05% as shown.
 
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Online dietert1

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Re: Statistical arrays
« Reply #112 on: July 26, 2019, 03:30:12 pm »
When i make a 10V - 7V divider from a 8x 5KOhm array using six resistors (2 resistors as 2.5 KOhm and 4 resistors as 5 KOhm) it will take 14 mW, which gives about 3 °C temperature increase. So i can run the Nomca at 40 °C. If the equations from the vishay paper apply in this low power regime, then i get an estimate of 290 ppm / 12,70 = 23 ppm, where 12.7 = 2 ** (150 °C - 40 °C) / 30 °C.
A change of -25 ppm has been observed in the drypack, so a 23 ppm number appears plausible to me. During the same drypack tests the division ratio of a divider optimized for low TC exhibited a change of 0,3 ppm of the division ratio.
To me it appears that vishay engineers were more or less focussed on durability in high humidity/high temperature regime, where it is easier to see real effects. In the meantime i can determine TC differences inside a Nomca array with a sigma of 0,08 ppm/K per resistor just from ambient temperature changes (delta T = 27 .. 29 °C),  without using the oven and i am getting results consistent with the oven measurements i did some weeks ago. Still no significant humidity effect on the division ratio after 3 weeks in the drypack.

As others noted before: The Nomca 1603 array in the Fluke/Wavetek 7000 reference means others have done these more detailed tests before and the Nomca part was found to be useful. Of course, as of to today there may be other, even better choices of thin film resistors. For example the Vishay PRA datasheet looks interesting. On its first page they claim "Very low noise < -35 dB and voltage coefficient < 0.01 ppm/V".

Regards, Dieter
 

Offline e61_phil

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Re: Statistical arrays
« Reply #113 on: July 26, 2019, 03:56:47 pm »
@Dieter: What do you mean by sigma? The standard deviation of your measurement? Or is it the error of the fit?
 

Online Kleinstein

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Re: Statistical arrays
« Reply #114 on: July 26, 2019, 04:01:47 pm »
The formula in the Vishay note on drift is only an approximation. It may or may not work very well for different types of resistors. Also the extension to much lower temperatures is speculative. Its more like tested from maybe 100 C - 250 C and increasingly uncertain at lower temperatures.

With the epoxy encapsulated parts, there is also another effect. The usual epoxies have a glass transition temperature somewhere in the 100 C - 160 C range. Things change when comparing the range well below (e.g. some 50 K) and above the glass transition temperature. At higher temperature there is some kind of equilibrium that can be reached, well below it is an increasingly slower drift towards a more dense state.
The rate of cool down from high temperature can have some effect - it kind of sets the disorder that is frozen in. Slower cooling from some 150 C (e.g. soldering) would work like a bun in. It's a window some 30-50 K below glass transition that is important. Burn in at higher temperature would cause new disorder, kind of resetting the clock.
Chances are the formula is for the higher temperature part, with the epoxy more or less in equilibrium.

The humidity is expected to mainly effect the epoxy, so there may not be much correlation with the high temperature drift.
 

Online dietert1

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Re: Statistical arrays
« Reply #115 on: July 26, 2019, 07:15:42 pm »
By sigma i meant standard deviation. The number given (0.08 ppm/K) is the standard deviation when comparing eight results of the oven measurements with the line fits of room temperature measurements. When i partition my recent measurements, i am getting similar standard deviations. There is no indication that the oven/box method results are different/worse than the ambient temperature results.
My uncertainties mean that the observed 0.3 ppm humidity effect of the divider isn't a real measurement but more like an upper limit.

Regards, Dieter
 
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Online imo

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Re: Statistical arrays
« Reply #116 on: August 10, 2019, 12:14:27 pm »
Here is a nice online app called "Resistor Network Finder":
http://kirr.homeunix.org/electronics/resistor-network-finder/

As the number of resistors in the network is limited to 6 and I want to use a bag of 10k resistors (+/-25ppm/C) only, I added several serial and parallel combinations of 10k to my list of "stocked resistors".

Interestingly, it looks it can find almost _any_ feasible value with such an approach..  :-+

My current understanding is the resistor's TCs within a lot (?) do follow somehow a "distribution" typical for the lot. Or do not?

« Last Edit: August 10, 2019, 01:03:13 pm by imo »
 
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Online dietert1

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Re: Statistical arrays
« Reply #117 on: August 30, 2019, 09:05:06 pm »
Got some more measurements on Nomca arrays. First i repeated measurements on the arrays A and F that have been in drypacks for about two months now, with very stable results. The 6 % reduction in absolute TC results from an improved temperature measurement.
From nine more arrays tested now the parts J, L and O exhibit low TCs and low TC spreads.

Regards, Dieter
 
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Offline doktor pyta

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Re: Statistical arrays
« Reply #118 on: April 19, 2020, 09:31:25 pm »
New candidate found. Should be better than NOMCA:
https://www.vishay.com/ppg?53033
especially PRA100I8 can be found on ebay.
 
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Offline Castorp

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Re: Statistical arrays
« Reply #119 on: July 15, 2020, 03:05:04 pm »
From the measurements quoted the NOMCA resistors as a 1:1 divider (3 x 10 K in parallel each) results in noise similar to the LTZ1000 noise in the 0.1 -10 Hz range  (noise power about doubles).

The < -30 dBi noise specs for the NOMCA are not really good. From the divider measurements they don't seem to be much better than specs.
For the temperature setting divider at the LTZ1000 this would still be well good enough, but not for a 7 to 10 V stage.

I've got some fresh measurements that confirm it. NOMCA and AORN, both Ta2N type, are within specs (-30 dB) but not significantly better. They are very noisy compared to most NiCr ones. Bulk metal foil (SMNZ) are better than -70 dB, so practically noiseless as expected.

These are all 10K arrays in Wheatstone bridge biased with +-10V. The bridge bias is reversed at 100 Hz and sampling (3458A, DCV mode, 9 ms aperture) is synchronized to it, then CDS is implemented in software.

The full results of these tests will be available some time next year.
« Last Edit: July 15, 2020, 03:07:13 pm by Castorp »
 
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Offline branadic

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Re: Statistical arrays
« Reply #120 on: July 15, 2020, 04:36:11 pm »
Can you eleborate on your test setup a little bit more? What is CDS standing for, correlated double sampling?

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Offline Castorp

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Re: Statistical arrays
« Reply #121 on: July 16, 2020, 06:51:12 am »
Can you eleborate on your test setup a little bit more? What is CDS standing for, correlated double sampling?

-branadic-

Yes, that's what it is. They have a good description in Linear AN96
https://www.analog.com/media/en/technical-documentation/application-notes/an96fa.pdf

In my setup I have two instrumentation amplifiers - INA163 for low impedances (<1 kOhm) and LT1167, selectable through a DPDT relay. Both amps are set for fixed gain of 100. After that there are two extra cascaded stages with G=10 for a total gain of up to 10000. So far I've taken all measurements with this highest gain setting, as the R arrays yield very decent CMRR (the worst one is about 86 dB). The bias voltages come from two Stanford SIM928 sources (isolated, battery-based). The bridge bias is switched through two ADG1404s. There's a bit of extra circuitry that clamps the instrumentation amp inputs during the bias reversal, to prevent large glitches and overdriving. It's all controlled by a small FPGA that also produces the sample trigger signal for the DVM. The R arrays are all soldered on identical small carrier boards that plug into the main board. Everything is covered, shielded, filtered, well decoupled, etc. That's it basically.
 
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Online Kleinstein

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Re: Statistical arrays
« Reply #122 on: July 16, 2020, 07:17:36 am »
Using AC excitation is a good idea to get lowest noise, as it avoids the 1/f noise of the amplifiers. And gets around chopper stabilized amplifiers.

Is the excitation directly coupled or like in the normal bridges for resistor noise readings galvanic isolated ?

The higher impedance instrumentation amplifiers however look relatively noisy. So there the classical isolated DC excitation with an chopper stabilized amplifier may be still competitive.

P.s. The AD8421 could be a lower noise alternative in the intermediate resistance range.
« Last Edit: July 16, 2020, 07:20:07 am by Kleinstein »
 

Offline Castorp

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Re: Statistical arrays
« Reply #123 on: July 16, 2020, 01:45:53 pm »
It's all DC coupled.

You're right, for intermediate source resistances there's a bit of amp noise added. Also for very low (<=100 Ohm), but I wouldn't bother getting something quieter than INA163. In the end it's not a big problem - that's just white noise. The interesting part of the spectra is 1/f, which is entirely due to the R arrays (when biased). Maybe in the final presentation of the data I'll RMS-subtract the known white noise contributions... or just explain their origins.
 
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