a-d converters electronics lecture 7
TRANSCRIPT
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Analog to Digital ConvertersElectronics Unit Lecture 7
Representing a continuously varying physical quantity by a sequence of
discrete numerical values.
03 07 10 14 09 02 00 04
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Conversion Methods(selected types, there are others)
Ladder ComparisonSuccessive Approximation
Slope Integration
Flash Comparison
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Ladder Comparison
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Single slope integration Charge a capacitor at constant
current
Count clock ticks
Stop when the capacitor voltagematches the input
Cannot achieve high resolution
Capacitor and/or comparator
-
+IN
C
R
S Enable
N-bit Output
Q
Oscillator Clk
Cou
nte
r
Start
Conversion
Start
Conversion
0
2
4
6
8
10
12
14
16
18
20
0 2 4 6 8 10 12 14 16
Time
Voltage
accro
ssthe
capacitor
Vin
Counting time
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Successive Approximation
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Flash Comparison
If N is the number of bits in the
output word.
Then 2N comparators will be
required.
With modern microelectronicsthis is quite possible, but will be
expensive.
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Pro and ConsSlope Integration & Ladder Approximation
Cheap but Slow
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Pro and ConsFlash Comparison
Fast but Expensive
Slope Integration & Ladder Approximation
Cheap but Slow
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Pro and ConsSuccessive Approximation
The Happy Medium ??
Slope Integration & Ladder Approximation
Cheap but Slow
Flash ComparisonFast but Expensive
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Resolution
Suppose a binary number with N bits is to
represent an analog value ranging from 0 to A
There are 2N possible numbers
Resolution = A / 2N
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Resolution Example
Temperature range of 0 K to 300 K to be linearly
converted to a voltage signal of 0 to 2.5 V, thendigitized with an 8-bit A/D converter
2.5 / 28
= 0.0098 V, or about 10 mV per step300 K / 28 = 1.2 K per step
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Resolution Example
Temperature range of 0 K to 300 K to be linearly
converted to a voltage signal of 0 to 2.5 V, thendigitized with a 10-bit A/D converter
2.5 / 210 = 0.00244V, or about 2.4 mV per step
300 K / 210 = 0.29 K per step
Is the noise present in the system well below 2.4 mV ?
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Quantization NoiseEach conversion has an average uncertainty of one-
half of the step size (A / 2N)
This quantization error places an upper limit on the
signal to noise ratio that can be realized.
Maximum (ideal) SNR 6 N + 1.8 decibels(N = # bits)
e.g. 8 bit 49.8 db, 10 bit 61.8 db
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Signal to Noise RatioRecovering a signal masked by noise
Some audio examples
In each successive example the noise power is reducedby a factor of two (3 db reduction), thus increasing the
signal to noise ratio by 3 db each time.
Example 1 Example 2 Example 3 Example 4
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Conversion TimeTime required to acquire a sample of the analogsignal and determine the numerical representation.
Sets the upper limit on the sampling frequency.
For the A/D on theBalloonSat board, TC 32 s,
So the sampling rate cannot exceed about 30,000samples per second (neglecting program overhead)
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Data Collection Sampling RateThe Nyquist RateA signal must be sampled at a rate at least twice that of the highest
frequency component that must be reproduced.
Example Hi-Fi sound (20-20,000 Hz) is generally sampledat about 44 kHz.
External temperature during flight need only be sampledevery few seconds at most.
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Activity E7a
Do the HuSAC
a party game for techies...
Human
Successive
Approximation
Converter
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Activity E7b
Data Acquisition Using BalloonSat