The non AZ mode adds extra low frequency noise, but it also samples the input all the time and this redues the noise bandwidth. Longer sampling also helps with noise from 236 signal source and getting better correlation with the 3458 DMM. The noise of the DIY ADC is only one part of the total noise and the extra 1/f noise seems to quite low. With the 236 in the 1.1 V range the noise is already quite a bit lower and there the extra 1/f noise from the non Az mode than gets important.
The RMS noise calculated from the mutiple reading to average is more of the higher frequency noise and does not include the extra 1/f noise that effects the non AZ readings. So for the +-1 V range the non AZ mode reading get a lower RMS noise, but still shows the more jagged (noisy) INL curve. For the full range the difference may not be so relevant as there is more noise from the 3458 and the K236 source.
The 1/f noise would be visible in the difference between runs.
The choice of AZ and non AZ mode should also effect the INL error due to the slow part of the DA in the integration capacitor: In the Az mode there is a charge carry over between the signal and zero reading and thus from positive to a negative effect. This increases the INL effect for the intermediate time scales (e.g. around 20 ms). With the non AZ mode the carry over is between one conversion and the next, nearly negating the effect of slow DA, especially the intermediate time scales.
The very similar INL error for the AZ and non AZ mode thus suggests that the slow DA is not the dominant contribution to the INL.
To be clear: The dataset is the same for AZ and non AZ evaluation, the raw values from adc are recorded (input & zero reading) and all processing is made offline.
The K238 (incl. 4th order LPF -3db@0.04Hz) does only contribute little noise, because the readings of ADC and DMM are correlated (isochronous equivalent acquisition) and the data processing works on those value pairs (triples with AZ).
There is no time interpolation done as usually, the differences between ADC and DMM are calculated on a per sample basis and aggregated into one datapoint for INL afterwards.
This was neccessary for the ability to ramp the input voltage continous to capture more voltage levels in one go and get the wiggly parts (bit like in the INL test between different run-ups).
This worked out somehow, but not good enough at that level were the INL is (noise from jitter exceeds 0.1ppm with 1000 rolling mean over input).
One of the best ramp INL-tests I got:
Processsing for one staircase is as follows (excerpt):
- Linear regression for dmm & adc
- Scaling adc from slope ratio of both regressions (gain normalization)
- Offset correction for adc
- Diffs between adc & dmm on a per sample basis gives INL (correlated)
- Aggregation to one point for INL