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Thomas Dehaeze 2024-07-16 08:58:32 +02:00
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content/zettels/analog_to_digital_converters.md
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@ -14,7 +14,7 @@ Tags
<https://dewesoft.com/daq/types-of-adc-converters> <https://dewesoft.com/daq/types-of-adc-converters>
- Delta Sigma <baker11_how_delta_sigma_adcs_work_part> - Delta Sigma (<a href="#citeproc_bib_item_1">Baker 2011</a>)
- Successive Approximation - Successive Approximation
@ -84,7 +84,7 @@ The quantization is:
{{< youtube b9lxtOJj3yU >}} {{< youtube b9lxtOJj3yU >}}
Also see <kester05_takin>. Also see (<a href="#citeproc_bib_item_2">Kester 2005</a>).
## Link between required dynamic range and effective number of bits {#link-between-required-dynamic-range-and-effective-number-of-bits} ## Link between required dynamic range and effective number of bits {#link-between-required-dynamic-range-and-effective-number-of-bits}
@ -96,12 +96,27 @@ Also see <kester05_takin>.
## Oversampling {#oversampling} ## Oversampling {#oversampling}
<lab13_improv_adc> (<a href="#citeproc_bib_item_3">Lab 2013</a>)
To have additional \\(w\\) bits of resolution, the oversampling frequency \\(f\_{os}\\) should be:
\begin{equation}
f\_{os} = 4^w \cdot f\_s
\end{equation}
### When Oversampling and Averaging Will Work {#when-oversampling-and-averaging-will-work}
> Key points to consider are:
>
> - The noise must approximate **white noise** with uniform power spectral density over the frequency band of interest.
> - The **noise amplitude must be sufficient** to cause the input signal to change randomly from sample to sample by amounts comparable to at least the distance between two adjacent codes (i.e., 1 LSB).
> - The input signal can be represented as a random variable that has equal probability of existing at any value between two adjacent ADC codes.
## Sigma Delta ADC {#sigma-delta-adc} ## Sigma Delta ADC {#sigma-delta-adc}
From <&schmidt20_desig_high_perfor_mechat_third_revis_edition>: From (<a href="#citeproc_bib_item_4">Schmidt, Schitter, and Rankers 2020</a>):
> The low cost and excellent linearity properties of the Sigma-Delta ADC have replaced other ADC types in many measurement and registration systems, especially where storage of data is more important than real-time measurement. > The low cost and excellent linearity properties of the Sigma-Delta ADC have replaced other ADC types in many measurement and registration systems, especially where storage of data is more important than real-time measurement.
> This has typically been the case in audio recording and reproduction. > This has typically been the case in audio recording and reproduction.
@ -125,4 +140,9 @@ Therefore, even though there are sigma-delta ADC with high precision and samplin
## Bibliography {#bibliography} ## Bibliography {#bibliography}
<./biblio/references.bib> <style>.csl-entry{text-indent: -1.5em; margin-left: 1.5em;}</style><div class="csl-bib-body">
<div class="csl-entry"><a id="citeproc_bib_item_1"></a>Baker, Bonnie. 2011. “How Delta-Sigma Adcs Work, Part.” <i>Analog Applications</i> 7.</div>
<div class="csl-entry"><a id="citeproc_bib_item_2"></a>Kester, Walt. 2005. “Taking the Mystery out of the Infamous Formula, $snr = 6.02 N + 1.76 Db$, and Why You Should Care.”</div>
<div class="csl-entry"><a id="citeproc_bib_item_3"></a>Lab, Silicon. 2013. “Improving the ADC Resolution by Oversampling and Averaging.” Silicon Laboratories.</div>
<div class="csl-entry"><a id="citeproc_bib_item_4"></a>Schmidt, R Munnig, Georg Schitter, and Adrian Rankers. 2020. <i>The Design of High Performance Mechatronics - Third Revised Edition</i>. Ios Press.</div>
</div>