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Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03 07 10 14 09 02 00 04 By: Engr. Muhammad Muizz Bin Mohd Nawawi

Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

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Page 1: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Analog to Digital Converters

Representing a continuously varying

physical quantity by a sequence of

discrete numerical values.

1

03 07 10 14 09 02 00 04

By: Engr. Muhammad Muizz Bin Mohd Nawawi

Page 2: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Successive Approximation

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Page 3: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Flash Comparison

3

If N is the number of bits in the

output word….

Then 2N comparators will be

required.

With modern microelectronics

this is quite possible, but will be

expensive.

Page 4: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Pro and Cons

Slope Integration & Ladder Approximation

Cheap but Slow

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Page 5: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Pro and Cons

Flash Comparison

Fast but Expensive

Slope Integration & Ladder Approximation

Cheap but Slow

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Page 6: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Pro and Cons

Successive Approximation

The Happy Medium ??

Slope Integration & Ladder Approximation

Cheap but Slow

Flash Comparison

Fast but Expensive

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Page 7: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

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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Page 8: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Resolution Example

Temperature range of 0 K to 300 K to be linearly converted to

a voltage signal of 0 to 2.5 V, then digitized with an 8-bit

A/D converter

2.5 / 28 = 0.0098 V, or about 10 mV per step

300 K / 28 = 1.2 K per step 8

Page 9: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Resolution Example

Temperature range of 0 K to 300 K to be linearly converted to

a voltage signal of 0 to 2.5 V, then digitized 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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Page 10: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Quantization Noise Each conversion has an average uncertainty of one-half of the step size ½(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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Page 11: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Signal to Noise Ratio Recovering a signal masked by noise

Some audio examples

In each successive example the noise power is reduced by a factor

of two (3 db reduction), thus increasing the signal to noise ratio by

3 db each time.

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Example 1 Example 2 Example 3 Example 4

Page 12: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Conversion Time

Time required to acquire a sample of the analog signal and

determine the numerical representation.

Sets the upper limit on the sampling frequency.

For the A/D on the BalloonSat board, TC ≈ 32 μs,

So the sampling rate cannot exceed about 30,000 samples

per second (neglecting program overhead) 12

Page 13: Analog to Digital Converters - Dunia ilmiah · Analog to Digital Converters Representing a continuously varying physical quantity by a sequence of discrete numerical values. 1 03

Data Collection – Sampling Rate

The Nyquist Rate

A 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 sampled at about

44 kHz.

External temperature during flight need only be sampled every few

seconds at most.

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