partitioning data acquisition systems (design conference 2013)

Advanced Techniques of Higher Performance Signal Processing

Partitioning Data Acquisition Systems

2

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3

Today’s Agenda

The dilemmas of system architecture and partitioning

Analog vs. digital signal processing

The perils of sampling

Digital vs. digital

Where to put all the processing functions Gain Sampling Filtering Multiplexing Special analog processing Isolation

4

Analog to Electronic Signal Processing

SENSOR(INPUT)

DIGITALPROCESSOR

AMP CONVERTER

ACTUATOR(OUTPUT)

AMP CONVERTER

5

… in the Beginning …

There was a sensor, mechanical driver, stylus, recording medium, playback stylus, and mechanical amplifier – it worked

6

… and Then We Added Electronics …

7

Current Day Integrated Functions

Audio codecs

SoundMAX® computer audio codecs

I/O ports

Mixed-signal front ends: modems, communications, CCD imaging, flat panel displays

Transmit and receive signal processors

Direct conversion radio

Energy metering

Video encoders/decoders, codecs

Touchscreen digitizers

Analog microcontrollers (high performance ADCs, DACs, and ARM µP core and flash memory)

Blackfin® DSPs with on-board ADCs and DACs

Motion sensors with embedded ADCs

8

The Dilemmas of Partitioning

Why Digitize at All?

Analog vs. Digital Processing Filtering Linearization Detection

Multiplexing Multiple amplifiers, filters, converters Simultaneous sampling

Signal Control Gain ranging vs. high resolution Compression Filtering

9

Analog and Digital DomainsWhy Convert to Digital?

Analog signals are continuous and provide the entire signal

Digital signals capture only a portion of the signal

Why digitize? Improved signal analysis potential More robust storage More accurate transmission Higher order filters implemented with less cost

Development objective of sampled data systems is to minimize effect of the sampling process

10

Analog vs. Digital Design

Analog Design Advantages Simpler and quicker to implement Lower power Analog systems don’t crash and need reboot

Disadvantages Difficult to change once in production – or at a customer Limited scale

Digital Design Advantages Changeable without hardware modification More filtering capability and scale Not sensitive to temperature

Disadvantages Initial software design takes longer More complex hardware Requires ADC that determines the SNR

11

Digital vs. Digital Design FPGA vs. DSP

FPGA Pros Deliver higher performance through very high parallelism Flexible I/O to support high-speed analog interfaces Low fixed costs Quick design turns for hardware changes

FPGA Cons Higher power in redundant logic Higher cost at volume

DSP Pros Programming is simpler – many libraries and third-party support companies Higher speed for straight processing

DSP Cons Fixed hardware structure Limited scale for parallel processing

12

The Costs of Digitizing Signals

You need to learn sampling theory

The input signal will be compromised – the goal is to determine what’s acceptable

The input signal needs to be filtered

Signal reconstruction will require another data converter

13

Many Types of Sampled Data Systems

Analog-to-Digital Converters

Digital-to-Analog Converters

Sample-and-Hold Amplifiers

Peak Detectors

Comparators

Switched Cap Filters

Samples a Continuous Signal

Domain Conversion Analog to digital Digital to analog Continuous time to discrete time Continuous frequency to discrete

frequency

Sampling Rate Continuous, discontinuous

14

Sampled Data System: Sampling and Quantization

LPFORBPF

N-BITADC

DSPN-BITDAC

LPFORBPF

fa

fs fs

t

AMPLITUDEQUANTIZATION DISCRETE

TIME SAMPLING

fa

1fsts=

15

RESOLUTIONN

2-bit

4-bit

6-bit

8-bit

10-bit

12-bit

14-bit

16-bit

18-bit

20-bit

22-bit

24-bit

2N

4

16

64

256

1,024

4,096

16,384

65,536

262,144

1,048,576

4,194,304

16,777,216

VOLTAGE(10V FS)

2.5 V

625 mV

156 mV

39.1 mV

9.77 mV (10 mV)

2.44 mV

610 V

153 V

38 V

9.54 V (10 V)

2.38 V

596 nV*

ppm FS

250,000

62,500

15,625

3,906

977

244

61

15

4

1

0.24

0.06

% FS

25

6.25

1.56

0.39

0.098

0.024

0.0061

0.0015

0.0004

0.0001

0.000024

0.000006

dB FS

– 12

– 24

– 36

– 48

– 60

– 72

– 84

– 96

– 108

– 120

– 132

– 144

*600nV is the Johnson Noise in a 10kHz BW of a 2.2k Resistor @ 25°C

Remember: 10-bits and 10V FS yields an LSB of 10mV, 1000ppm, or 0.1%.All other values may be calculated by powers of 2.

Quantization: The Size of a Least Significant Bit (LSB)

16

Practical Resolution Needs for Data Converters

Instrumentation Measurements Sensor resolution/accuracy of 0.5% = 1/200 8 bits equivalent to 1/256 -- digitizing will lose information 10x sensor resolution = 1/2000 -- 12 bits is 1/4096 Allows discrimination of small changes Can also be driven by display requirements

Dynamic Signal Measurements Audio systems need better than 0.1% distortion at 5% of full scale Equivalent to 1/20,000 -- 16 bits is 1/65,536

17

Ideal ADC Sampling3 Different Frequencies, Sampled the Same

18

Ideal ADC SamplingOnce Sampled, Information Is Lost

19

Baseband Antialiasing Filter Requirements

A

DR

fs

fa fs - fa

fs2

STOPBAND ATTENUATION = DR

TRANSITION BAND: fa to fs - fa

CORNER FREQUENCY: fa

Antialias Filter Prevents Aliasing

Contributes to Dynamic Range

Antialias Filter Objectives Brick Wall (Steep/Deep Rolloff) Linear Passband Linear Phase

20

A Key Partitioning Question—Where to Filter?

Analog Filtering Hardware oriented—generally fixed design

Digital Filtering Software oriented—offers more flexibility

21

Purposes of Filtering

Noise Reduction Typically low-pass

Discrimination and Selection RF detection – channel separation Extracting small signals from noise

Signal Enhancement Music

Filter Complexity Derives from the Requirement

22

Types of Filters

Types of Analog filters Active

More common at lower frequencies Passive

More common at higher frequencies

Types of Digital filters IIR (infinite impulse response)

Based on analog filters More computationally efficient

FIR (finite impulse response) Can be linear phase More computationally intensive Can provide more power and flexibility

Digital filtering requires digitizing—which requires an analog anti-aliasing filter before the analog-to-digital converter

23

Comparing Analog and Digital Filters

Analog No computational limitations

to limit high frequency operation

Subject to component drift and accuracy

Simpler circuit Unlimited dynamic range Basically no latency

Digital Computations must be

completed in sampling time— limits real-time operation

Not subject to component drift and accuracy

More complex circuit Requires antialiasing filter,

ADC, DSP, DAC, and reconstruction filter

Dynamic range limited by converter resolution

Much higher latency (delay) Some filter functions can only

be done digitally

Analog vs. Digital Filter Frequency Response Comparison

Digital Filtering

26

Throughput Considerations for Digital Filters

A digital biquad is a second-order recursive linear filter containing two poles and two zeros

Determine how many biquad sections (N) are required to realize the desired frequency response

Multiply this by the number of instruction cycles per biquad for the DSP and add overhead cycles

The result (plus overhead) is the minimum allowable sampling period (1 / fs) for real-time operation

Comparison Between IIR and FIR Filters

28

Sigma-delta ADC -- the multi-purpose part

Sigma-delta ADCs span the analog and digital world

Provide customized filtering and high-resolution data conversion

The core of digital audio processing

29

Sigma-Delta ADC - First-Order Modulator

å ò +

_

+VREF

–VREF

DIGITALFILTERANDDECIMATOR

+

_

CLOCKKfs

VINN-BITS

fs

fs

A

B

1-BIT DATASTREAM1-BIT

DAC

LATCHEDCOMPARATOR(1-BIT ADC)

1-BIT,

Kfs

SIGMA-DELTA MODULATOR

INTEGRATOR

Sampled Data System: Sampling and Quantization

31

Simplified Frequency Domain Linearized Model of a Sigma-Delta Modulator

åANALOG FILTER

H(f) = 1f

åX Y

+

_

X – Y1f

( X – Y )Q = QUANTIZATIONNOISE

Y = 1f

( X – Y ) + Q

REARRANGING, SOLVING FOR Y:

Y = Xf + 1

+ Q ff + 1

SIGNAL TERM NOISE TERM

Y

32

Oversampling, Digital Filtering, Noise Shaping, and Decimation

fs2

fs

Kfs2

Kfs

KfsKfs2

fs2

fs2

DIGITAL FILTER

REMOVED NOISE

REMOVED NOISE

QUANTIZATIONNOISE = q / 12 q = 1 LSBADC

ADCDIGITALFILTER

SDMOD

DIGITALFILTER

fs

Kfs

Kfs

DEC

fs

NyquistOperation

Oversampling+ Digital Filter+ Decimation

Oversampling+ Noise Shaping+ Digital Filter+ Decimation

A

B

C

DEC

fs

33

Data Acquisition Subsystem Configuration

Multiplexing Multiple preamps Multiple anti-alias filters Multiple ADCs

Gain Adjustable gain per channel PGA vs. high resolution ADC

Simultaneous Sampling Multiple signals correlated in time

Noise Reduction/Antialiasing Filter Placement

Special Analog Processing

Isolation

34

Data Acquisition Subsystem ConfigurationMultiplexing

Multiplexing is done to reduce system cost by using fewer ADCs ADC is fast enough to handle all channels in sequence ADC errors are the same for all channels

Multiplexing issues Settling time after switching channels Multiplexer impedance may compromise signal Final buffer amplifier may be needed Multiplexer switching transients

Correlated sampling may require a faster solution How close in time sampling needs to be done Nyquist theory determines how often each signal needs to be sampled Total signal throughput rate Simultaneous sampling at lower rates Simultaneous conversion at higher rates

35

Simple ADC Multiplexing—AD7298

8 inputs plus temp sensor and single track/hold

TEMPSENSOR

12-BITSUCCESSIVE

APPROXIMATIONADC

INPUTMUX

T/H

VDD GND

PD/RST

SCLKDOUTDIN

CS

VDRIVE

VIN7

VIN0

CONTROLLOGIC

SEQUENCER

VREF

BUFREF

AD7298

08

754

-001

T

36

Simultaneous Sampling—AD7606 8 Track/Hold Inputs Sampled Together

V1

V1GND

RFB1MΩ

1MΩ RFB

CLAMP

CLAMP SECOND-ORDER LPF

T/H

V2

V2GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V3

V3GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V4

V4GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V5

V5GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V6

V6GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V7

V7GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

V8

V8GND

RFB1MΩ

1MΩ RFB

CLAMP


T/H

8:1MUX

AGND

BUSY

FRSTDATA

CONVST A CONVST B RESET RANGE

CONTROLINPUTS

CLK OSC

REFIN/REFOUT

REF SELECT

AGND

OS 2

OS 1

OS 0

DOUTA

DOUTB

RD/SCLK

CS

PAR/SER/BYTE SEL

VDRIVE

16-BITSAR

DIGITALFILTER

PARALLEL/SERIAL

INTERFACE

2.5VREF

REFCAPB REFCAPA

SERIAL

PARALLEL

REGCAP

2.5VLDO

REGCAP

2.5VLDO

AVCCAVCC

37

Full High Speed Dual Sampling—AD96432 Complete Sampling ADCs at 170 MHz

14

14

REFERENCE

SERIAL PORT

SCLK SDIO CSB CLK+ CLK– SYNC

1 TO 8CLOCKDIVIDER

AD9643

VIN+A D0±

D13±

DCO±

OR±

PDWN

OEB

VIN–A

VIN+B

VCM

VIN–B

NOTES1. THE D0± TO D13± PINS REPRESENT BOTH THE CHANNEL A

AND CHANNEL B LVDS OUTPUT DATA.

AVDD AGND DRVDD

096

36

-001

.

.

.

.

.PARALLELDDR LVDS

ANDDRIVERS

PIPELINE14-BITADC

PIPELINE14-BITADC

Positioning the Noise Reduction Filter to Reduce the Effects of the Op Amp Noise

ADCs often have very high input bandwidths, usually greater than fs/2 Low distortion drive amplifiers typically have high bandwidths Placing a simple LPF or BPF placed between the amp and the ADC is

an excellent noise reduction technique Filter output impedance must be able to drive ADC The output capacitor of the filter absorbs some of the ADC input

transient currents.

2.38

fFILTER

AMP

AMP

LPFORBPF

LPFORBPF

ADC

ADC

fFILTERfs

fs

fCL

fCL

fADC

fADC

(A)

(B)

Amp noise integratedover amp BW or ADC BW, whichever is less

Amp noise integratedover filter noise bandwidth only

39

Where to Put the Gain?

Partitioning question about using PGA vs. high resolution ADC

PGA with wide-range gain steps can extend effective resolution of ADC Provides fine resolution Not an exact solution unless gain ranges are perfectly matched Nonlinearity induced between ranges

Not as popular with advent of higher resolution ADCs

Still useful in certain applications

40

ADC Multiplexing with Programmable Gain— AD7194

16 inputs plus temp sensor and programmable gain amplifier

Accommodates sensors with widely varying signal levels

DVDD DGND REFIN1(+) REFIN1(–)

AIN1/P3AIN2/P2

AIN3/P1/REFIN2(+)AIN4/P0/REFIN2(–)

AINCOM

AD7194

SERIALINTERFACE

ANDCONTROL

LOGIC

REFERENCEDETECT

TEMPSENSOR

DOUT/RDY

DIN

SCLK

CS

MCLK1 MCLK2

CLOCKCIRCUITRY

AVDD AGND

AIN5

AIN16

Σ-ΔADC

PGAMUX

085

66

-001

AVDD

AGND

41

Special Analog Processing and Special Cases

Certain sensors require specialized analog processing to extract precise measurements Thermocouples—cold-junction compensation Wide-dynamic-range photodiodes—signal compression Linearization

Some sensors require precision tuning per unit—others can be tuned together

Calibration and replacement issues

Digital options—store adjustment coefficients in software

Isolation Analog or digital Power isolation

42

Thermocouples

Thermocouples require cold-junction compensation Traditionally done with specialized amplifiers with internal temperature sensors Newer techniques use high-accuracy temperature sensors and A-D converters

to allow compensation at the processor

Thermocouple non-linearity is non-linear Difficult to construct analog compensation Digital systems use look-up tables

Detailed analysis in the Low-Level Signal Acquisition session

43

High Accuracy Multichannel Thermocouple Measurement Solution (CN0172)

Log Amplifiers

Signal compression Many applications must capture signals over a very wide dynamic range

Radio antennas capturing broadcast signals Photomultipliers and photodiodes capture light signals over a very wide range

To process and use these signals, they need to be compressed to a much smaller range

Logarithmic amplifiers Log amplifiers compress signals over ranges of as much as 120db – a million

to one -- to a normal range of 1 to 10 volts Accuracy is typically 0.1 to 0.5 dB -- 1 to 5%

Digital compression alternative Programmable gain amplifier combined with high-resolution ADC Can achieve range out to 120dB Limited at very high frequencies

Log Amp Transfer Function

IDEAL

ACTUAL

SLOPE = VY

2VY

VY

IDEAL

ACTUAL

VYLOG (VIN/VX)

+

-VIN=VX

VIN=10VX VIN=100VXINPUT ONLOG SCALE

VOUT = VY log10

0

VIN

VX

IDEAL

ACTUAL

SLOPE = VY

2VY

VY

IDEAL

ACTUAL

VYLOG (VIN/VX)

+

-VIN=VX

VIN=10VX VIN=100VXINPUT ONLOG SCALE

VOUT = VY log10

0

VIN

VX

Log Amplifier Accuracy

5

4

3

2

1

–4

–5

500MHz

100MHz

10MHz

–3

–2

–1

0

–80 –70 –60 –50 –40 –30 –20 –10 0 10 20

ER

RO

R(d

B)

INPUT LEVEL (dBm)

AD8307 covers 80dB with 0.5dB accuracy

AD8307 six-decade RF power measurement

TOANTENNA

VP

604Ω

100kΩ1/2W

NC

2kΩ

VR12kΩ

INT ±3dB

51pF

51pF

0.1µF

NC

OUTPUT

LEAD-THROUGH

CAPACITORS,1nF

1nF

NC = NO CONNECT

+5V

VOUT

AD8307INP VPS ENB INT

INM COM OFS OUT

8 7 6 5

2 3 41

50Ω INPUTFROM P.A.

1µW TO1kW

22Ω

48

Oversampled SAR ADC with PGA Achieving Greater Than 125 dB Dynamic Range (CN0260)

Dynamic gain ranging

Faster than high-resolution sigma delta

Sampling rate up to 2.5MSPS

49

Oversampled SAR ADC with PGA Achieving Greater Than 125 dB Dynamic Range (CN0260)

50

Where to Put the Isolation?

Isolation is used to galvanically separate systems Safety in patient monitoring High-voltage systems Remove high common-mode noise

Most commonly done at the digital level ADC converter signal to digital Transmitted across digital isolators

Providing power to isolated circuits needed

High-voltage amplifiers suitable in some motor control or power control systems

More detail in the Data and Power Isolation session

51

500 V Common-Mode Voltage Current Monitor (CN0218)

AD8212

52

Bidirectional Isolated High-Side Current Sense with 270 V Common-Mode Rejection (CN0240)

53

Novel Analog-to-Analog Isolator Using an Isolated Sigma-Delta Modulator, Isolated DC-to-DC Converter, and Active Filter (CN0185)

54

Reverse Partitioning

Smarter peripheral devices sensing local conditions

Make local decisions to off-load main processor

Reduce programming load

Automatic gain control

Power control

55

Reverse Partitioning—AD5755

Quad 16-bit DAC for 4–20 mA industrial signaling

Dynamic power control for thermal management

On-chip diagnostics

AD5755

AVSS–15V AGND

AVDD+15V

AVCC5.0V

DVDD

DGND

LDAC

CLEAR

SCLKSDIN

SYNCSDO

FAULT

DC-TO-DCCONVERTER

POWERCONTROL

INPUTSHIFT

REGISTERAND

CONTROL

STATUSREGISTER

POWER-ONRESET

REFERENCEBUFFERS

DACREG A

INPUTREG A

VREF

WATCHDOGTIMER

(SPI ACTIVITY)

ALERT

REFOUT

REFIN

AD1

AD0

DAC A1616

SWA VBOOST_A

GAIN REG A

OFFSET REG A

R1

R2 R3

RSET_A

VOUT_A

IOUT_B, IOUT_C, IOUT_D

RSET_B, RSET_C, RSET_D

+VSENSE_B, +VSENSE_C, +VSENSE_D

VOUT_B, VOUT_C, VOUT_D

IOUT_A

+VSENSE_A

–VSENSE_A

DAC CHANNEL B

DAC CHANNEL A

DAC CHANNEL C

DAC CHANNEL D

SWB, SWC, SWD VBOOST_B, VBOOST_C, VBOOST_D

7.4V TO 29.5VREG

VSEN1 VSEN2

+

07

30

4-0

01

VOUTRANGE

SCALING

56

Flexible 4-Channel Analog Front End for Wide Dynamic Range Signal Conditioning (CN0251)

This circuit has it all

Multiplexing front-end

Multiplexer buffer

Instrumentation amplifier for CMRR

Anti-alias filter

Funnel amplifier to fit ADC range

Internal programmable gain amplifier Gain ranges trimmed and matched

Sigma-delta ADC provides noise shaping

57

Flexible 4-Channel Analog Front End for Wide Dynamic Range Signal Conditioning (CN0251)

D3V3DGND

DGND AGND

–IN

IA

RGRG*

*OMIT RG FOR G = 1

RG

+IN

+VS

VOUT

REF

–VS

AD8226

ADP1720

–OUTVN

VP

+OUT

NC

+IN 0.4x

–IN 0.8x

+IN 0.8x

–IN 0.4x

–VS

+VS1kΩ

1.25kΩ 100Ω

100kΩ

100Ω1.25kΩ

1kΩ

AD8475

1.25kΩ

1.25kΩ

MCLK1

NC

MCLK2

P0/

RE

FIN

2(–)

P1/

RE

FIN

2(+

)

DVDD DGND

RE

FIN

1(+

)

RE

FIN

1(–)

AIN2AIN1AIN3AIN4AINCOM

BPDSW

AGND

AD7192

TEMPSENSOR

AVDD

AGND

DOUT/RDY

DIN

SCLK

CS

SYNC

P3

P2

AVDDAGND

Σ-ΔADCM

UX

DOUT

DIN

SCLK

CS

SYNC

P3

P2

ADG1409

S1A

S4B

DA1nF

IN OUTGND

1nF

10nF

4.02kΩ

4.02kΩ

DB

S4A

S1B

VS1A

VS4B

VS4A

VS1B

1-OF-4DECODER

A0GND A1

VDD

+15VA

EN VSS

–15VA

–15VA

+5VA330µH @ 100MHz

A4V096

+5VA

+15VA

0.1µF

10nF

10nF

1µF

0.1µF

0.1µF

10µF

0.1µF

+15VA

+5VA

VOCM VOCM

ADR444

AD8475

VIN VOUT

GND

+15VA

A4V096

PGA

D3V3

D3V3

DGND

1µF

0.1µF0.1µF

SERIALINTERFACE

ANDCONTROL

LOGIC

CLOCKCIRCUITRY

10

351

-001

2

1

1

2

7

6

45

8

3

4

10

12

18 19 15 16

23

24

3

4

5

617

9 1 2 7 8

25

2120

11

13

14

10

9

8

3

7

5

6

58 Tweet it out! @ADI_News #ADIDC13

What We Covered

The dilemmas of system architecture and partitioning

Analog vs. digital signal processing

The perils of sampling

Digital vs. digital

Where to put all the processing functions Gain Sampling Filtering Multiplexing Special analog processing Isolation


Visit the Flexible 4-Channel Analog Front End for Wide Dynamic Range Signal Conditioning (CN0251) in the Exhibition Room

This flexible signal conditioning circuit is for processing signals of wide dynamic range, varying from several mV p-p to 20 V p-p. The circuit provides the necessary conditioning and level shifting and achieves the dynamic range using the internal programmable gain amplifier (PGA) of the high resolution analog-to-digital converter (ADC).

Image of demo/board

This demo board is available for purchase: www.analog.com/DC13-hardware

http://www.analog.com/DC13hardware


FMComms1 Demo in the Exhibition Hall

New partitioning concepts for radio

Ubuntu Linux on ZC702

FMComms1 on FMC

HDMI Display and USB Keyboard/Mouse

Full Transmit and Receive

Image of demo/board

This demo board is available for purchase: www.analog.com/DC13-hardware

http://www.analog.com/DC13hardware

partitioning data acquisition systems (design conference 2013)

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