1. Automation Building BlocksBy
Ed Red
Sensors
Analyzers
Actuators
Drives
Vision systems

2. Objectives To review basic building blocks for implementing automation
To consider application conditions
To introduce assessment criteria
To test understanding of the material presented

3. Process control

4. Inductive proximity sensors
Building Blocks
Sensors
Analyzers
Actuators
Drives
Vision system (integrated sensor/analyzer)
Inductive proximity sensors

5. Sensors: closed loop systems

6. Sensors: open loop?

7. Sensors: many types (Table 6.2)

8. Building Blocks – sensor features
Accuracy and repeatability
Precision
Range
Response time
Calibration methods
Minimum drift
Costs and reliability
Sensitivity

9. Building Blocks – sensors & moving objects
We can characterize a sensor’s capability by it’s operating frequency or by its response time. Both determine how well the sensor might measure the desired property (proximity, length…) of a moving object. Using a sensor’s specification, how might we determine how fast a moving object might move past the sensor and the sensor still read the object parameter correctly?

10. Building Blocks – sensor devices
See Table 6.2 for in depth description!
Photoelectric sensors
Proximity switches (inductive and capacitive)
Range sensors (ultrasonic/acoustic, laser reflectors…)
Transducers (encoders)
Linear encoder
Inductive proximity sensors
Absolute rotary encoder

11. Building Blocks – analyzers
Encoder example – An absolute optical encoder has 8 rings, 8 LED sensors, and 8 bit resolution. If the output pattern is , what is the shaft’s angular position?
Ring Angle (deg) Pattern Value (deg) Total

12. Building Blocks – drives
Stepper Motors (index by open-loop control)
AC/DC servomotors (PID feedback control, holds torque when at rest)
Kinematic devices (intermittent operation, e.g., Geneva mechanism)
Digital drives

13. Building Blocks – present drives Motion Planning & Control
Controller
Servocard
Motion Planning & Control
Servo-loops
Application
Set Points
Amplifiers

14. Building Blocks – digital drives
Microprocessors and Digital Signal Processors (DSP’s) are replacing analog components with digital components (i.e., digital drives).
EIA RS-431, the outdated ±10V standard, no longer need constrain control resolution.
Revolutions in computer operating systems, applications, and networking.
Networking standards, such as IEC and IEEE 1394, are changing motion control architectures and hardware configurations.
Need for A/D and D/A interfaces is rapidly declining, being replaced by a high- speed network between the master host (a PC) and the distributed digital slave devices.

15. Building Blocks – digital drives
Ormec’s servowire implementation of IEEE 1394
DMAC

16. If direction is to be changed, requires another PWM signal.
PWM and digital drives (binary control!)
PWM – Pulse Width Modulation - a constant frequency, two-valued signal (e.g., voltage) in which the proportion of the period for which the signal is on and the period for which it is off can be varied.
Percentage of time on is called the duty cycle.
Voltage value will depend on the application
PWM frequency must be high enough so that motor cannot respond to a single PWM signal
If direction is to be changed, requires another PWM signal. On
Off
T 2T 3T 4T
25% duty cycle
50% duty cycle

17. A/D Signal Conversion
Resolution of A/D is represented by number of conversion bits n:
Nq = number of quantitization levels = 2n
R = conversion resolution = Voltage range/(Nq – 1) (± 10 V)
± R
Variable (or Voltage)
Time

18. A/D Signal Conversion
Successive approximation method is similar to the method we used to extract the encoder value from the binary output but backwards. Here is simple example:
Range (± 10 V) Quantitizations Bit (on or off) Value
6.8 V
= error V

19. D/A Signal Conversion The decoding equation is:
Eo = Eref [0.5 B B B3+…+(2n)-1Bn]
where
Eo = output analog signal value
Eref = ref voltage
For example: means B1 = 1, B2 = 0, B3 = 0, B4 = 1, B5 = 0

20. Electromagnetism B I I F l B F = I l x B
Current flow produces magnetic field and associated flux.
Changing field (flux) through a coil induces a reactive electromotive force (emf) e:
e = -N dF/dt (Faraday’s Law) N = # turns in coil; F is flux in webers
This in turn generates an induced current in opposite direction and a resulting opposing flux as described by:
e = -L di/dt L = inductance in henrys

21. AC motors Induction motor video
Stator structure is composed of steel laminations shaped to form poles around which are wound copper wire coils. These primary windings connect to, and are energized by, the voltage source to produce a rotating magnetic field. Three-phase windings spaced 120 electrical degrees apart are popular in industry.
Rotor (or rotating secondary) is another assembly of laminations over a steel shaft core. Radial slots around the laminations’ periphery house rotor bars—cast-aluminum or copper conductors shorted at one end and positioned parallel to the shaft (see photo).
The motor’s name comes from the alternating current (ac) “induced” into the rotor by the rotating magnetic flux produced in the stator. Motor torque is developed from interaction of currents flowing in the rotor bars and the stator’s rotating magnetic field.
Induction motor video

22. (new tech) Linear motors
Two basic classes: 1) permanent magnet (PM) brushless, and 2) asynchronous linear induction motors (LIMs).
PM brushless motors abound in various subclasses, such as the moving coil and moving magnet types. Ironless refers to a core containing only copper coils (and epoxy encapsulation). Smooth "cog-free" motion is produced since no attractive force exists between coil and magnet--but at the cost of lower force output.
Tubular linear motor
Slot-less refers to a special design of steel laminations where the windings go through holes in the stator rather than slots. The result is a smoother surface facing the magnet. This design also reduces cogging by eliminating variation in attractive force.
Tubular linear motors roll up the unit about an axis parallel to its length. In one style, an outer thrust block carrying the motor coils envelops and moves along a stationary thrust rod that houses magnets. Another style has a central rod with magnets that moves relative to an outer stator member. Travel is limited since the thrust rod must be supported at both ends (or at one end for the moving-rod version).

23. IEEE 1394, USB2, Fiber Optic, etc. Motion Planning & Control
Digital Drive Network PC
Motion Planning & Control
Windows Application
Controls Application
DCI
Set Points
CPU 2 RTOS
CPU 1
Control Servo
DMAC

24. Building Blocks Assessment
Who are major vendors of proximity switches, servomotors?
What are the limits to sensor proximity distances?
What types of proximity accuracies might you expect from proximity sensors?
Which sensors work on which materials?
Are sensors affected by speed by which materials move past them?
What are weight to torque ratios for common servomotors?

25. Building Blocks Assessment
What does torque speed curve look like for the motors typically used to control robots?
What is difference between absolute encoder and relative encoder? How do encoders measure directional changes?
What is difference between a resolver and digital encoder?
Costs of sensors, motors, etc.?
How do the new linear drives work, and what are their response characteristics?

26. Building Blocks – machine vision
Algorithm PC
Definition – “Machine vision is the capturing of an image (a snapshot in time), the conversion of the image to digital information, and the application of processing algorithms to extract useful information about the image for the purposes of pattern recognition, part inspection, or part positioning and orientation”….Ed Red

27. Building Blocks – machine vision
Equipment:
Computer
Frame grabber
Camera (CCD array)
Lenses
Lighting
Calibration templates
Algorithms
Types:
Front
Back
Side
Structured
Strobe

28. Machine Vision – structured lighting
Structured Lighting is used in a front lighting mode for applications requiring surface feature extraction. Structured lighting is defined as the projection of a crisp line of light onto an object. The patterned light is then used to determine the 3-D characteristics of an object from the resulting deflections observed.
Note the non-typical approach of projecting a grid array of light on an object to detect features

29. Machine Vision – image processing
Segmentation – Define and separate regions of interest
Thresholding – Convert each pixel into binary (B or W) value by comparing bit intensities
Edge detection – Locate boundaries between objects
Feature extraction – Determine features based on area and boundary characteristics of image
Pattern recognition – Identify objects in midst of other objects by comparing to predefined models or standard values (of area, etc.)

30. Machine Vision – applications
Dimensional measurement
Object verification
Proper position/orientation
Flaws and defects
Counting
Guidance and control (offsets, tracking)

31. Machine Vision – example
8-bit image of metallic iron as it appears in iron ore (lighter objects in the image represent the metallic iron)
Histogram displays pixel intensity distribution …background appears at gray level 40, ore shows up at gray level 70, and high-intensity iron turns up at gray levels above 150. Image clearly differentiates components.
Blob analysis - set threshold to gray level 148…all the pixels with gray levels of 148 or lower get set to zero. Pixels with gray levels of 149 or higher get set to one
Morphology functions slightly change or eliminate the shapes of objects so imaging software can easily count them.

32. Machine Vision – example
Suppose we wish to calculate the area and centroid of the selected binary region in the last figure, how would you do it? Assume that you have a camera such that the pixels are square and you have a matrix of pixel values as depicted in the figure shown.
What equations would you apply? Y X

33. Machine Vision Assessment
Who are major vendors of vision systems and the various components?
What are typical camera resolutions?
What are typical camera calibration techniques?
What is camera distortion?
Is color vision imaging used? In what applications?
How long does it take to process images? As a function of image processing function?
What are typical costs for imaging systems? For frame grabbers, cameras, lenses, lighting?

34. Building Blocks
What have we learned?