Download CS244- Introduction to embedded systems and ubiquitous

CS244-Introduction to
Embedded Systems and
Ubiquitous Computing
Instructor: Eli Bozorgzadeh
Computer Science Department
UC Irvine
Winter 2010
CS244 – Lecture 7
Sensors, Actuators and Other
hardware components
Winter 2010- CS 244
2
Simplified Block Diagram
actuators
ICS212 WQ05 (Dutt) Hardware Components: Sensors,
Actuators, Converters
Sensors and Actuators

Sensors:




Capture physical stimulus (e.g.,
heat, light, sound, pressure,
magnetism, or other mechanical
motion)
Typical generate a proportional
electrical current
May require analog interface
solenoid
mic
speaker
Actuators


Convert a command to a physical
stimulus (e.g., heat, light, sound,
pressure, magnetism, or other
mechanical motion)
May require analog interface
laser diode/transistor compass
dc motor
accelerometer
Sensors

Processing of physical data starts with capturing this
data.

Sensors can be designed for virtually every physical
stimulus


heat, light, sound, weight, velocity, acceleration, electrical
current, voltage, pressure, ...
Many physical effects used for constructing sensors.


law of induction (generation of voltages in an electric
field),
light-electric effects.
Example: Acceleration Sensor
 MEMS device
 Small mass in
center
 When accelerated:

Mass displaced from
center
 Resistance of wires
connected to mass
change
 Detect change in
resistance and model
acceleration
Courtesy
& ©: S. Bütgenbach, TU
Braunschweig
Charge-coupled devices (CCD)
Image Sensors: Based on charge transfer to next pixel cell
CMOS Image Sensors
Based on standard production process for CMOS
chips, allows integration with other components.

Source: B. Diericks: CMOS image sensor concepts.
Photonics West 2000 Short course (Web)
Comparison CCD/CMOS sensors
Example: Biometric Sensors
Example: Fingerprint sensor (© Siemens, VDE):
Integrated into ID mouse.
Example: Artificial eyes
© Dobelle Institute
(www.dobelle.com)
Artificial eyes (2)
He looks hale, hearty, and healthy — except for the
wires. They run from the laptops into the signal
processors, then out again and across the table and
up into the air, flanking his face like curtains before
disappearing into holes drilled through his skull.
Since his hair is dark and the wires are black, it's
hard to see the actual points of entry. From a
distance the wires look like long ponytails.
© Dobelle Institute
(www.dobelle.com)
Other examples of sensors

Heart monitoring sensors

“Managing Care Through the Air”


Rain sensors for wiper control





Touch pads/screens
Proximity sensors


High-end autos
Pressure sensors


IEEE Spectrum Dec 2004
Collision avoidance
Engine control sensors
Audio sensors
Motion sensors
Thermal sensors

SARS detection (“high fever”)
Simplified Block Diagram
actuators
Sensors and Actuators

Sensors:




Capture physical stimulus (e.g.,
heat, light, sound, pressure,
magnetism, or other mechanical
motion)
Typical generate a proportional
electrical current
May require analog interface
solenoid
mic
speaker
Actuators


Convert a command to a physical
stimulus (e.g., heat, light, sound,
pressure, magnetism, or other
mechanical motion)
May require analog interface
laser diode/transistor compass
dc motor
accelerometer
Actuators

Output physical stimulus varies in range and
modality

Large (industrial) control actuators


Optical output





Pneumatic systems: physical motion
IR
Thermal output
Small motor controllers (stepper motors)
MEMS devices
List goes on…..
Stepper Motor Controller

Stepper motor: rotates fixed number of degrees
when given a “step” signal

In contrast, DC motor simply rotates when power applied,
and coasts to stop

Rotation achieved by applying specific voltage
sequence to coils

Controller greatly simplifies this
MEMS Actuators
Huge variety of actuators and output devices.
Microsystems motors as examples (© MCNC)
(Dimensions in the order of several microns)
(© MCNC)
Actuators
Courtesy and ©:
E. Obermeier, MAT,
TU Berlin
Simplified Block Diagram
actuators
Sample-and-Hold Circuit
Model:
Vx = Ve when Clock = 1
Sampling: how often the signal is converted.
Quantization: how many bits used for sampling.
Aliasing
Potential Consequence of sampling, e.g.:
Signal frequency: 5.6 Hz
Sampling frequency: 9 Hz
1.5
1
0.5
0
-0.5
-1
-1.5
aliasing
Winter 2010- CS 244
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Analog to Digital Conversion

Sampling: how often is the signal converted?


Quantization: how many bits used to represent a sample?




Twice as high as the highest frequency signal present in the input
Sufficient to provide required dynamic range
Under-loading: dynamic range not used properly
Clipping: input signal beyond the dynamic range
Aliasing: erroneous signals, not present in analog domain, but
present in digital domain


Use anti-aliasing filters
Sample at higher than necessary rate
5.0V
4.5V
4.0V
3.5V
3.0V
2.5V
2.0V
1.5V
1.0V
0.5V
0V
1111
1110
1101
1100
1011
1010
1001
1000
0111
0110
0101
0100
0011
0010
0001
0000
proportionality
4
4
3
3
analog output (V)
Vmax = 7.5V
7.0V
6.5V
6.0V
5.5V
analog input (V)
Analog-to-Digital Converter
2
1
t1
0100
t2
t3
time
t4
1000 0110 0101
Digital output
analog to digital
2
1
t1
t2
0100
t3
1000 0110
Digital input
digital to analog
t4
time
0101
Flash A/D Converter
Parallel comparison
with reference voltage
 Speed:
O(1)
 HW complexity: O(n)


ICS212 WQ05 (Dutt) Hardware
Components: Sensors,
Actuators, Converters
n= # of distinguished
voltage levels
Frequency Domain

Any continuous time varying
signal can be represented
as the sum of cosine
functions of different
amplitude and frequency


E.g., input signal captured as
the sum of 4 cosine functions
Once in frequency domain,
certain manipulations
become trivial (e.g., filtering)
ICS212 WQ05 (Dutt) Hardware
Components: Sensors,
Actuators, Converters
Simplified Block Diagram
actuators
ICS212 WQ05 (Dutt) Hardware Components: Sensors,
Actuators, Converters
Digital-to-Analog (D/A) Converters
Various types, can be quite simple,
e.g.:
ICS212 WQ05 (Dutt) Hardware
Components: Sensors,
Actuators, Converters
Reference


Embedded system design by Peter Mardewel
(Chapter: Embedded System Hardware)
Embedded System (Foundation for cyber
physical systems) by Peter Mardewel, online
book through UCI connection, Chapter:
Embedded Hardware. (pg. 119-132).
Winter 2010- CS 244
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