Control Mechanism Of Linear Electric Actuator For 3D Image Processing Application.
ii
DECLARATION
“I hereby declare that the work in this thesis is my own except for summaries and
quotations which have been duly acknowledged.”
Signature:
………………..
Author:
LEE SEK ENN
Date:
………………..
iii
To my beloved mother and father
iv
ACKNOWLEDGEMENT
First of all, I would like to express my deepest appreciation to my supervisor,
Dr. Cheng See Yuan, and Dr Soo Yew Guan for providing me explanations and
guidances me throughout the entire PSM process. Without the sharing and help from
him, it would be extremely difficult to proceed in this study. Therefore, it is definitely
an honor of mine to be able to have him as my supervisor.
Secondly, I would also like to thank my university, Universiti Teknikal
Malaysia Melaka (UTeM), and my faculty, Faculty of Mechanical Engineering, for
giving me an opportunity to gain more knowledge in the last four years.
Furthermore, I would like to express my sincere gratitude to my friends and
Hoo who accompanied me throughout the entire learning process in UTeM. They gave
me a lot of advices and encouragement. I may have hard time struggling in my studies
if I did not meet them.
Last but not least, I would like to take this opportunity to thank my family
members especially my parents. They showered me with love and care throughout the
entire process. Without persistent encouragement from them, I would not be able to
reach this stage. I am greatly indebted to my family members for not giving up on me
and have faith in me.
v
ABSTRACT
This project address the usage of electric linear actuators on the application of
visual inspection such as 3D image processing. Visual inspection such as
photogrammetry were widely used since mid-1980 due to its automated operation that
can eliminate the error occurs by inspection using traditional method, which is the
inspection of products with simple measuring devices. However, visual inspection that
carried out in industrial application without stop the production line would be
beneficial due to minimizing loss in terms of costs and time. A model of linear electric
actuators is presented to illustrate the potential of performance in obtain same speed
with the inspected object that travelled on conveyor belt. Constant velocity is requested
and method of obtaining was being controlled by AC servo motor controller that are
presented in this project. Fully automatically operation is likely to perform. However,
this cannot be carried out due to incompatibility of equipment. For the next research,
it is highly recommended to check the compatibility between the equipment.
vi
ABSTRAK
Projek ini menujukan penggunaan penggerak elektrik linear dalam aplikasi
pemeriksaan visual seperti pemprosesan imej 3D. Pemeriksaan visual ini amat popular
pada pertengahan 1980-an atas operasi penggunaan yang automatik di mana boleh
meningkatkan prestasi dalam proses pemeriksaan. Pemeriksaan visual yang boleh
dijalankan tanpa perlu menghentikan proses pengeluaran akan memberikan manfaat
dari segi masa dan kos. Sebuah model penggerak elektrik linear disediakan untuk
menguji prestasi dalam menyesuaikan kelajuan penggerak dengan objek yang
diperiksa yang terletak di atas ‘conveyor belt’. Objektif projek ini adalah untuk
mendapatkan halaju yang tetap dengan menggunakan ‘AC servo motor controller’.
Operasi yang automatik amat digalakkan tetapi untuk kajian ini, operasi secara
automatik tidak dapat dilaksanakan atas sebab kegagalan dari segi peralatan. Oleh itu,
pemeriksaan terhadap fungsi dan operasi peralatan tidak patut diringankan untuk
kajian seterusnya.
vii
TABLE OF CONTENTS
CHAPTER
CHAPTER 1
CHAPTER 2
TITLE
PAGE
DECLARATION
ii
ACKNOWLEDGEMENT
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF FIGURES
x
LIST OF TABLES
xii
LIST OF SYMBOLS
xiii
LIST OF APPENDIXES
xiv
INTRODUCTION
1.1
Background
1
1.2
Problem Statement
2
1.3
Objectives
2
1.4
Scope
2
LITERATURE REVIEW
2.1
Research Background
3
2.2
Overview of Inspection System
3
2.3
Photogrammetry
5
2.3.1
Close range Photogrammetry
7
2.3.2
Technical Issues of Photogrammetry
8
2.3.3
Photogrammetric Cameras
9
2.3.4
SLR Cameras
10
2.3.5
Camera Calibration
10
viii
2.3.6
2.4
Accuracy and Verification
Automated Inspection on Moving
11
11
Conveyor
2.4.1
System Set-up for the Non
12
Contact Measurement Approach Structure
2.4.2
Automated Headlamp Lens Inspection
13
2.4.3
System Configuration
15
2.5
Digital Image Matching
15
2.6
Design for Actuator
17
2.7
Design of Speed Controller for DC Motor Drive
18
2.7.1
2.8
CHAPTER 3
Mathematical Modeling of DC Motor Drive 18
Servo Motor
19
METHODOLOGY
3.1
3.2
3.3
Overview of measuring system components
25
3.1.1
Parallel Interface
26
3.1.2
Camera Module
26
3.1.3
Camera Pan and Tilt
27
3.1.4
Direction of Movement
27
3.1.5
Software
27
Selection of Measurement
27
3.2.1
Ac Servo Motor Controller
27
3.2.2
Linear Electric Actuator
28
3.2.3
Raspberry Pi
31
3.2.4
Proximity Sensor
33
Method of Operation
34
3.3.1
Initialization
34
3.3.2
Direct Measurement Approach
34
3.3.2.1 Speed of Conveyor Belt
35
3.3.2.2 Speed of Linear Actuator
36
Analysis of Linear Actuator through Test
38
3.3.3
Mode
3.3.4
Targeting Object
39
3.3.5
Solving the Problem
40
ix
CHAPTER 4
RESULT AND ANALYSIS
41
4.1
Program Written in Program Operation Mode
41
4.2
Images Captured by Running the Program
44
CHAPTER 5
DISCUSSION
49
CHAPTER 6
CONCLUSION AND RECOMMENDATION
51
REFERENCES
52
APPENDIX A
56
APPENDIX B
58
APPENDIX C
61
x
LIST OF FIGURES
NO.
TITLE
PAGE
2.1
Aerial photogrammetry
2.2
Close range photogrammetry
2.3
Examples of photogrammetric cameras
9
2.4
Examples of photogrammetric multi- camera systems
9
2.5
Examples of digital SLR cameras
10
2.6
Visual classification setup in an industrial setting
12
2.7
Configuration for in line inspection calibration
12
2.8
Plastic lens with punctual defect
14
2.9
The proposed sensor planning system
14
2.10
The optimal system configuration which required symmetric
15
.
6
.
7
angle of 45⁰ between cameras and the similar positioning for the lamps.
2.11
Schema of the algorithm for reconstruction of surface with
17
discontinuity by digital image matching technique
2.12
Block diagram of closed loop control of DC motor
19
2.13
Design of Motor- Stator
23
2.14
Design of Motor – Rotor
23
2.15
Design of Motor – Encoder
24
3.1
Schematic diagram of setup configuration
25
3.2
Overview of setup configuration
26
3.3
Ac Servo Motor
28
3.4
Electric linear actuator
30
3.5
Raspberry Pi and Raspberry Pi camera mounted on the special custom
32
made table
3.6
Proximity sensor light up when the object pass through it
33
3.7
Performance data of conveyor belt
35
xi
3.8
Jog test mode
36
3.9
Positioning test mode
36
3.10
High Speed Monitor and positioning test mode
37
3.11
Speed graph of linear actuator with highest speed.
38
3.12
Speed graph of linear actuator with highest speed
39
3.13
Pin number of the controller
40
4.1
Program write in Program Operation Mode
43
4.2
Actuator start moving in backward direction
43
4.3
Actuator start moving in forward direction
43
4.4
1st set of image of object being transported on conveyor belt at 1200r/min 44
4.5
2nd set of image of object being transported on conveyor belt at 1200r/min 44
4.6
3rd set of image of object being transported on conveyor belt at 1200r/min 45
4.7
1st set of image of object being transported on conveyor belt at 200r/min
4.8
2nd set of image of object being transported on conveyor belt at 200r/min 45
4.9
3rd set of image of object being transported on conveyor belt at 200r/min 46
4.10
Comparison of 1st set image between stationary and moving
45
46
actuator at 1200r/min
4.11
Comparison of 2nd set image between stationary and moving
47
actuator at 1200r/min
4.12
Comparison of 3rd set image between stationary and moving
47
actuator at 1200r/min
4.13
Comparison of 1st set image between stationary and moving
48
actuator at 200r/min
4.14
Comparison of 2nd set image between stationary and moving
48
actuator at 200r/min
4.15
Comparison of 3rd set image between stationary and moving
actuator at 200r/min
48
xii
LIST OF TABLES
NO.
TITLE
2.1
Comparison types of driving devices .
2.2
Comparison Table of Motors
3.1
Tabulation of data
PAGE
20
.
21
38
xiii
LIST OF SYMBOLS
rpm
=
Revolution per minute
W
=
Watt
Hz
=
Hertz
mm
=
Millimeter
cm
=
Centimeter
MB
=
Mega Byte
a
=
Acceleration, mm/s2
ms
=
Acceleration, ms
s
=
Second
x10STMµm
=
Pulse per revolution
xiv
LIST OF APPENDIXES
NO.
TITLE
PAGE
A
Application Summary of Servo Motor
56
B
Signal Wiring of AC Servo Motor
58
C
Grantt Chart
61
1
CHAPTER 1
INTRODUCTION
1.1
Background
Products quality and delivery reliability are the key factor success in
manufacturing industry (Colledani et al., 2014). In order to deliver high quality
products, inspection is very important but traditional approach like labour- intensive
methods results in increasing manufacturing lead time and production cost, as well as
delay in detecting an out of control limit (Fundamentals, Inspection, & Machine, n.d.).
However there is another kind of visual inspection approach that mainly deal with
surface quality, maximum defect size and detection of defects on surfaces, such as
crack, corrosion, damaged part on a components assembly (Li & Gu, 2004). Besides,
optical visual inspection can executed very fast with no human interference and
constant, which are significant advantages of achieving production monitoring
(Kosmopoulos & Varvarigou, 2001). So photogrammetric measurement (as a part of
visual inspection) regarded as accepted 3D measurements tools that has been a
possibility for quality control with direct input of image information into computers
(Clarke et al., n.d.). Somehow, development of fully automatic photogrammetric
measurement would be more benefit to in- line industrial inspection. Thus, motorized
linear slide that allow image capturing device move spontaneously with the conveyor
belt is introduced to accomplish the objective of this project. Control mechanism is
access through Ac Servo Motor Controller. Manual dimensioning and tracing work
can be replace by capture surfaces of design models (Mat et al., 2009).
2
1.2
Problem Statement
To speed up production rate and improve product quality, products inspection
has to be carried out with higher accuracy at shorter duration of time. Thus, non–
contacting 3D modeling reconstruction such as photogrammetry appear to be a good
avenue (Uffenkamp, n.d.). However, in a continuous manufacturing process, a product
is being delivered in a continuous manner. Dealing with a moving target causes a
motion effect (i.e. Blurring) on the acquired images (Zappa et al., 2014). Therefore, a
controllable electric linear actuator that can move simultaneously with the conveyer
belt is necessary. By doing so, camera mounted on the electric linear actuator can move
at the same speed as the rate of product that being delivered on the conveyer belt.
Hence, blurring of image eliminated.
1.3
Objectives
i)
To optimize the AC Servo Motor controller of motorized linear actuator for
image base 3D modeling application
ii)
To design varies mechanisms of controlling the speed, timing and positioning
linear slider of image capturing device of photogrammetry.
iii)
To access the performance of each control mechanisms.
1.4
Scope
The scope of this project is to design a controller that can be used to control
the speed of a motorized linear actuator that move spontaneously with the conveyer
belt. The efficiency and the performance of the motorized linear actuator with
implementation of control methodology will be assessed. Ac Servo Motor controller
using MR configurator software are the focus of the project.
3
CHAPTER 2
LITERATURE REVIEW
2.1 Research Background
Standard method for complex 3D measurement tasks need to have object with
a high number of object points. Close range photogrammetry offered potential
measurement with convergent multi- image configurations (Luhmann, 2010).
Inspection of incoming parts with no human interface can be done but this required at
the finished assemblies and photogrammetry is usually done when the products is in
static condition. To make it in time inspection at the early stage without stopping the
production line, actuators to run corresponding with the conveyor belt is designed for
the visual inspection. However highly precision position and speed controls are needed
especially in motion control equipment (Rashidi et al., 2015). Types of actuators are
compared of its function and advantages in application. .Furthermore, controller
should have design with load/ friction compensation, disturbance rejection against
parameter variations in addition to accuracy (Rashidi et al., 2015). Basically the
objective of controller is to make system to reach the optimum position.
2.2 Overview of Inspection System
Products quality and delivery reliability are key factors for success in
manufacturing industry (Colledani et al., 2014). Challenge faced such as delivering the
required production rate of high quality products by minimizing resources in terms of
human power and mechanical power (F. Puente Leo, 2006). Usually traditional
4
approach of inspection method uses measurement such as ruler, calipers, and meter
ruler and so on. Therefore manufacturers look for reliable and consistent automated
visual inspection of their products to reduce manual involvement in inspection. Not
only this, labor intensive methods will result in increase of manufacturing lead time
and production cost, as well as significant delay in detecting the defects
(Fundamentals et al., n.d.).
Basically, finish inspection and in-line inspection are the two main inspection
performed by machining industries. Finish inspection can only performed the work at
the end of the machining process in a special quality room where in- line inspection is
performed at the production line (Ayub et al., 2014).
The advantages of in-line inspection are the identification deviations from the
nominal values, detection absence of vital parts of properties and detection products
out of tolerance at the early stage in manufacturing process to prevent from further
machining, handling, assembly, etc. In addition, information on deviations from target
values may be fed back to process (Ayub et al., 2014).
Among those inspection processes, visual inspection is another kind of
inspection approach that mainly deals with surface quality and maximum defect size.
Defects on surfaces, such as cracks, corrosion, damaged part on a component assembly
also part of visual inspection (Li & Gu, 2004). In the meantime, there are quite of areas
visual inspection have extended to. For an example, areas of robot guidance, inspection
of incoming parts or finished assemblies in application of inspection, part
identification, guidance and control (Ayub et al., 2014). Significant advantages of an
optical visual inspection are it can executed very fast with no human interference and
constant, thus 100% monitoring of the production can be achieved (Kosmopoulos &
Varvarigou, 2001). Lest not, direct input of image information into computers is the
development of fully automated photogrammetric measurement (as a part of visual
inspection). This discover been a possibility for quality control which would be benefit
in industrial inspection (Clarke et al., n.d.).
In many successful and diverse applications, photogrammetry can be regarded
as fully accepted 3D measurements tools. Field of industry, biomechanics, chemistry,
5
biology, archeology, architecture, automotive and aerospace engineering, as well as
accident reconstruction have practiced
photogrammetry (Jiang et al., 2008).
According to Satorres Martínez et al., (2009), different types of defects are detected
based on the design of algorithms which are more towards its geometry and
dimensions. Large variety of industrial application areas also apply photogrammetric
system, including;
Automotive manufacturing, for car body deformation measurement, control of
supplier parts, adjustment of tooling and rigs, establishment of control point
networks, crash testing, etc.;
Aerospace industry, for measurement and adjustment of mounting rigs,
antenna measurement, part-to-part alignment, etc.;
Wind energy systems for deformation measurements and production control;
Engineering and construction, for measurement of water dams, tanks, plant
facilities, etc.
2.3 Photogrammetry
By using camera, digital representing of real object in form of point cloud is a
technique of photogrammetry (Daaam, 2010). In other word, reliable information
about the properties of surfaces and objects is able to obtain through photogrammetry
without physical contact with the objects. The name “photogrammetry” is derived
from three Greek words phos or phot which means light, gramma means letter or
something drawn, and metrein is the noun of measure (Schenk, 2005).
Fundamental principle of photogrammetry is triangulation. Used images can
be divided into stereo photogrammetry and single image photogrammetry. “Lines of
sight” can developed from each camera to points of object by overlapping two or more
images from at least two locations and 3D structure of object reconstructed is defined
as stereo photogrammetry. Stereo photogrammetry is excellent to obtain three
dimensional information for the objects from registered images that are two
dimensional which can be done by intersection of these lines of sight mathematically
6
from the three dimensional coordinates of the points of interest (“Geodetic Systems,
Inc,” n.d.). Second type would be monoscopic photogrammetry (also called as single
image photogrammetry) where information of objects is presented by using monoplotting methods (Marinov, 2003).
On the basic, photogrammetry also divided into two categories: aerial and
terrestrial photogrammetry. Images such as topographic maps and land use details
acquired via overhead shots from an aircraft are known as aerial photogrammetry (Fig.
2.1). Terrestrial photogrammetry is further defined as close range photogrammetry
(Fig. 2.2), an approach where camera generally pointing towards the center of the
object with highly convergent camera orientations when the object size and the camera
distance are both less than 100m (Jiang et al., 2008).
Figure 2.1: Aerial photogrammetry.
(Source: Marinov, 2003)
7
Figure 2.2: Close range photogrammetry.
(Source: Marinov, 2003)
2.3.1
Close range Photogrammetry
Close range photogrammetry become technically and economical successful in
the mid-1980s due to its first breakthrough in automated and high accurate 3D
measurements. Large volume objects with high number of object points can be
obtained based on the convergent multi-image configurations, digital comparators and
digital image processing of the scanned imagery as close range photogrammetry
offered the potential of measurement precision to 1: 500,000. By this, performance of
photogrammetry could be become standard method for complex 3D measurement
tasks (Luhmann, 2010).
8
2.3.2
Technical Issues of Photogrammetry
To form an efficient and economic system, number of technical components
required to succeed use of photogrammetry in industry. Therefore, components and
related technical issues summaries as the following list:
Imaging sensor: resolution (number of pixels), acquisition and data transfer
speed, camera stability, synchronization and etc.;
Targeting and illumination: interested object featured, target shape and size,
and measurement volume;
Image configuration: number of camera stations, desired measurement
accuracy, redundancy, robustness, self- calibration ability, and self- control of
orientation and calibration;
Image processing: automation of target recognition and identification, subpixel measurement of target center, multi-image, matching approaches, and
feature tracking;
3D reconstruction: 3D coordinates determination method (e.g. spatial
intersection, bundle adjustment) and error statistics;
Data interfaces: integration into CAD/ CAM environments, machine and data
interfaces and etc.;
Verification of accuracy: reference bodies, reference data, standards and
guidelines and acceptance tests.
Setup of complex tasks is illustrated in above lists for an appropriate design,
operation of close-range industrial photogrammetry systems. Besides, basic camera
concepts, system designs and measurement tasks for industrial photogrammetry also
presented. An overview of recent technology and applications provided rather than
comprehensive coverage due to large variety of applications and system configurations
is discussed (Luhmann, 2010).
9
2.3.3
Photogrammetric Cameras
Cameras with stable interior orientation and high accuracy are demanded to
reduce need of periodic or on-the-job calibration, and technical possibility for
simultaneous camera calibration. Besides the classical ‘metric camera’, rarely few
cameras are mainly for photogrammetry application. However, limitation of ‘metric
camera’ is it only is used in conjunction with the desired accuracy level of camera.
Photogrammetric cameras (Fig. 2.3 and Fig. 2.4) are designed for high- accuracy
industrial metrology. In the meantime, the integrated processors enable 3D
measurements in off-line (1 camera) or on-line (2 camera) mode (Luhmann, 2010).
Figure 2.3: Examples of photogrammetric cameras.
(Source: Luhmann, 2010).
Figure 2.4: Examples of photogrammetric multi- camera systems.
(Source: Luhmann, 2010).
10
2.3.4
SLR Cameras
High- resolution digital SLR cameras with sensors between 10 and 60
Megapixel are designed for fast and simple photogrammetric work because of its range
of exchangeable lenses, high capacity storage devices and powerful batteries.
Somehow, camera calibration is an important step in the complete process chain as
their mechanical stability is usually poor and with changing interior orientation
(Luhmann, 2010). Classical small format (35mm SLR) are offered by companies such
as Nikon, Canon and Sony are mainly used for off-line applications. The two sample
cameras are shown in Fig. 2.5.
Figure 2.5: Examples of digital SLR cameras.
(Source: Luhmann, 2010)
2.3.5
Camera Calibration
Since accuracy is directly related to sensor quality and correct modeling of
interior orientation, camera calibration is an essential of photogrammetric systems in
industrial application (Luhmann, 2010). Somehow, there would be some difficulties
faced in calibration as stated in following cases:
Camera geometry unstable during image acquisition (e.g. gravity effects)
Geometric configuration of images does not allow bundle adjustment with selfcalibration (e.g. due to weak intersection angle or lack of camera rotation)
11
Objects does not provide enough information (e.g. points, distances) for
calibration
Besides, three or more control points as the datum of object can be introduces
as well as introducing shape constraints in photogrammetric orientation (Luhmann,
2010). Otherwise, image-wise of the camera will be calibrated if the mechanical
instability of the camera is worse than the required accuracy level. As long as the
imaging configuration consists of enough well distributed images, the position of
perspective center is usually adjusted for each image while the distortion values are
kept constant for all images as to enhance the accuracy. Furthermore, precision of
camera calibration can be determined from precision of image and object points, or by
standard deviations of camera parameters (Luhmann, 2010).
2.3.6
Accuracy and Verification
Two most important practical considerations are the specified accuracy of an
industrial measurement system and the achieved accuracy within a real project. Final
accuracy figures can be manipulated simply by increasing the number of observations
in many photogrammetric applications. Furthermore, photogrammetric measured
distances are compared to their calibrated nominal length for the accuracy test. Further
developments of high precision industrial close range photogrammetry is challenging
in industrial photogrammetry (Luhmann, 2010).
2.4 Automated Inspection on Moving Conveyor
Nowadays, manufacturing is very high competitive with automation in quality
control processes (Kosmopoulos & Varvarigou, 2001; Leones et al., 2005). This
included on the moving conveyor, some sort of automated visual processing and
classification of items placed are required in many industrial applications. An
overview of the typical setup is shown in Fig. 2.6 which camera located above
conveyer belt which view the items orthographically. Classification of items placed
are done by the item separator that placed before the camera so the incoming items are
DECLARATION
“I hereby declare that the work in this thesis is my own except for summaries and
quotations which have been duly acknowledged.”
Signature:
………………..
Author:
LEE SEK ENN
Date:
………………..
iii
To my beloved mother and father
iv
ACKNOWLEDGEMENT
First of all, I would like to express my deepest appreciation to my supervisor,
Dr. Cheng See Yuan, and Dr Soo Yew Guan for providing me explanations and
guidances me throughout the entire PSM process. Without the sharing and help from
him, it would be extremely difficult to proceed in this study. Therefore, it is definitely
an honor of mine to be able to have him as my supervisor.
Secondly, I would also like to thank my university, Universiti Teknikal
Malaysia Melaka (UTeM), and my faculty, Faculty of Mechanical Engineering, for
giving me an opportunity to gain more knowledge in the last four years.
Furthermore, I would like to express my sincere gratitude to my friends and
Hoo who accompanied me throughout the entire learning process in UTeM. They gave
me a lot of advices and encouragement. I may have hard time struggling in my studies
if I did not meet them.
Last but not least, I would like to take this opportunity to thank my family
members especially my parents. They showered me with love and care throughout the
entire process. Without persistent encouragement from them, I would not be able to
reach this stage. I am greatly indebted to my family members for not giving up on me
and have faith in me.
v
ABSTRACT
This project address the usage of electric linear actuators on the application of
visual inspection such as 3D image processing. Visual inspection such as
photogrammetry were widely used since mid-1980 due to its automated operation that
can eliminate the error occurs by inspection using traditional method, which is the
inspection of products with simple measuring devices. However, visual inspection that
carried out in industrial application without stop the production line would be
beneficial due to minimizing loss in terms of costs and time. A model of linear electric
actuators is presented to illustrate the potential of performance in obtain same speed
with the inspected object that travelled on conveyor belt. Constant velocity is requested
and method of obtaining was being controlled by AC servo motor controller that are
presented in this project. Fully automatically operation is likely to perform. However,
this cannot be carried out due to incompatibility of equipment. For the next research,
it is highly recommended to check the compatibility between the equipment.
vi
ABSTRAK
Projek ini menujukan penggunaan penggerak elektrik linear dalam aplikasi
pemeriksaan visual seperti pemprosesan imej 3D. Pemeriksaan visual ini amat popular
pada pertengahan 1980-an atas operasi penggunaan yang automatik di mana boleh
meningkatkan prestasi dalam proses pemeriksaan. Pemeriksaan visual yang boleh
dijalankan tanpa perlu menghentikan proses pengeluaran akan memberikan manfaat
dari segi masa dan kos. Sebuah model penggerak elektrik linear disediakan untuk
menguji prestasi dalam menyesuaikan kelajuan penggerak dengan objek yang
diperiksa yang terletak di atas ‘conveyor belt’. Objektif projek ini adalah untuk
mendapatkan halaju yang tetap dengan menggunakan ‘AC servo motor controller’.
Operasi yang automatik amat digalakkan tetapi untuk kajian ini, operasi secara
automatik tidak dapat dilaksanakan atas sebab kegagalan dari segi peralatan. Oleh itu,
pemeriksaan terhadap fungsi dan operasi peralatan tidak patut diringankan untuk
kajian seterusnya.
vii
TABLE OF CONTENTS
CHAPTER
CHAPTER 1
CHAPTER 2
TITLE
PAGE
DECLARATION
ii
ACKNOWLEDGEMENT
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF FIGURES
x
LIST OF TABLES
xii
LIST OF SYMBOLS
xiii
LIST OF APPENDIXES
xiv
INTRODUCTION
1.1
Background
1
1.2
Problem Statement
2
1.3
Objectives
2
1.4
Scope
2
LITERATURE REVIEW
2.1
Research Background
3
2.2
Overview of Inspection System
3
2.3
Photogrammetry
5
2.3.1
Close range Photogrammetry
7
2.3.2
Technical Issues of Photogrammetry
8
2.3.3
Photogrammetric Cameras
9
2.3.4
SLR Cameras
10
2.3.5
Camera Calibration
10
viii
2.3.6
2.4
Accuracy and Verification
Automated Inspection on Moving
11
11
Conveyor
2.4.1
System Set-up for the Non
12
Contact Measurement Approach Structure
2.4.2
Automated Headlamp Lens Inspection
13
2.4.3
System Configuration
15
2.5
Digital Image Matching
15
2.6
Design for Actuator
17
2.7
Design of Speed Controller for DC Motor Drive
18
2.7.1
2.8
CHAPTER 3
Mathematical Modeling of DC Motor Drive 18
Servo Motor
19
METHODOLOGY
3.1
3.2
3.3
Overview of measuring system components
25
3.1.1
Parallel Interface
26
3.1.2
Camera Module
26
3.1.3
Camera Pan and Tilt
27
3.1.4
Direction of Movement
27
3.1.5
Software
27
Selection of Measurement
27
3.2.1
Ac Servo Motor Controller
27
3.2.2
Linear Electric Actuator
28
3.2.3
Raspberry Pi
31
3.2.4
Proximity Sensor
33
Method of Operation
34
3.3.1
Initialization
34
3.3.2
Direct Measurement Approach
34
3.3.2.1 Speed of Conveyor Belt
35
3.3.2.2 Speed of Linear Actuator
36
Analysis of Linear Actuator through Test
38
3.3.3
Mode
3.3.4
Targeting Object
39
3.3.5
Solving the Problem
40
ix
CHAPTER 4
RESULT AND ANALYSIS
41
4.1
Program Written in Program Operation Mode
41
4.2
Images Captured by Running the Program
44
CHAPTER 5
DISCUSSION
49
CHAPTER 6
CONCLUSION AND RECOMMENDATION
51
REFERENCES
52
APPENDIX A
56
APPENDIX B
58
APPENDIX C
61
x
LIST OF FIGURES
NO.
TITLE
PAGE
2.1
Aerial photogrammetry
2.2
Close range photogrammetry
2.3
Examples of photogrammetric cameras
9
2.4
Examples of photogrammetric multi- camera systems
9
2.5
Examples of digital SLR cameras
10
2.6
Visual classification setup in an industrial setting
12
2.7
Configuration for in line inspection calibration
12
2.8
Plastic lens with punctual defect
14
2.9
The proposed sensor planning system
14
2.10
The optimal system configuration which required symmetric
15
.
6
.
7
angle of 45⁰ between cameras and the similar positioning for the lamps.
2.11
Schema of the algorithm for reconstruction of surface with
17
discontinuity by digital image matching technique
2.12
Block diagram of closed loop control of DC motor
19
2.13
Design of Motor- Stator
23
2.14
Design of Motor – Rotor
23
2.15
Design of Motor – Encoder
24
3.1
Schematic diagram of setup configuration
25
3.2
Overview of setup configuration
26
3.3
Ac Servo Motor
28
3.4
Electric linear actuator
30
3.5
Raspberry Pi and Raspberry Pi camera mounted on the special custom
32
made table
3.6
Proximity sensor light up when the object pass through it
33
3.7
Performance data of conveyor belt
35
xi
3.8
Jog test mode
36
3.9
Positioning test mode
36
3.10
High Speed Monitor and positioning test mode
37
3.11
Speed graph of linear actuator with highest speed.
38
3.12
Speed graph of linear actuator with highest speed
39
3.13
Pin number of the controller
40
4.1
Program write in Program Operation Mode
43
4.2
Actuator start moving in backward direction
43
4.3
Actuator start moving in forward direction
43
4.4
1st set of image of object being transported on conveyor belt at 1200r/min 44
4.5
2nd set of image of object being transported on conveyor belt at 1200r/min 44
4.6
3rd set of image of object being transported on conveyor belt at 1200r/min 45
4.7
1st set of image of object being transported on conveyor belt at 200r/min
4.8
2nd set of image of object being transported on conveyor belt at 200r/min 45
4.9
3rd set of image of object being transported on conveyor belt at 200r/min 46
4.10
Comparison of 1st set image between stationary and moving
45
46
actuator at 1200r/min
4.11
Comparison of 2nd set image between stationary and moving
47
actuator at 1200r/min
4.12
Comparison of 3rd set image between stationary and moving
47
actuator at 1200r/min
4.13
Comparison of 1st set image between stationary and moving
48
actuator at 200r/min
4.14
Comparison of 2nd set image between stationary and moving
48
actuator at 200r/min
4.15
Comparison of 3rd set image between stationary and moving
actuator at 200r/min
48
xii
LIST OF TABLES
NO.
TITLE
2.1
Comparison types of driving devices .
2.2
Comparison Table of Motors
3.1
Tabulation of data
PAGE
20
.
21
38
xiii
LIST OF SYMBOLS
rpm
=
Revolution per minute
W
=
Watt
Hz
=
Hertz
mm
=
Millimeter
cm
=
Centimeter
MB
=
Mega Byte
a
=
Acceleration, mm/s2
ms
=
Acceleration, ms
s
=
Second
x10STMµm
=
Pulse per revolution
xiv
LIST OF APPENDIXES
NO.
TITLE
PAGE
A
Application Summary of Servo Motor
56
B
Signal Wiring of AC Servo Motor
58
C
Grantt Chart
61
1
CHAPTER 1
INTRODUCTION
1.1
Background
Products quality and delivery reliability are the key factor success in
manufacturing industry (Colledani et al., 2014). In order to deliver high quality
products, inspection is very important but traditional approach like labour- intensive
methods results in increasing manufacturing lead time and production cost, as well as
delay in detecting an out of control limit (Fundamentals, Inspection, & Machine, n.d.).
However there is another kind of visual inspection approach that mainly deal with
surface quality, maximum defect size and detection of defects on surfaces, such as
crack, corrosion, damaged part on a components assembly (Li & Gu, 2004). Besides,
optical visual inspection can executed very fast with no human interference and
constant, which are significant advantages of achieving production monitoring
(Kosmopoulos & Varvarigou, 2001). So photogrammetric measurement (as a part of
visual inspection) regarded as accepted 3D measurements tools that has been a
possibility for quality control with direct input of image information into computers
(Clarke et al., n.d.). Somehow, development of fully automatic photogrammetric
measurement would be more benefit to in- line industrial inspection. Thus, motorized
linear slide that allow image capturing device move spontaneously with the conveyor
belt is introduced to accomplish the objective of this project. Control mechanism is
access through Ac Servo Motor Controller. Manual dimensioning and tracing work
can be replace by capture surfaces of design models (Mat et al., 2009).
2
1.2
Problem Statement
To speed up production rate and improve product quality, products inspection
has to be carried out with higher accuracy at shorter duration of time. Thus, non–
contacting 3D modeling reconstruction such as photogrammetry appear to be a good
avenue (Uffenkamp, n.d.). However, in a continuous manufacturing process, a product
is being delivered in a continuous manner. Dealing with a moving target causes a
motion effect (i.e. Blurring) on the acquired images (Zappa et al., 2014). Therefore, a
controllable electric linear actuator that can move simultaneously with the conveyer
belt is necessary. By doing so, camera mounted on the electric linear actuator can move
at the same speed as the rate of product that being delivered on the conveyer belt.
Hence, blurring of image eliminated.
1.3
Objectives
i)
To optimize the AC Servo Motor controller of motorized linear actuator for
image base 3D modeling application
ii)
To design varies mechanisms of controlling the speed, timing and positioning
linear slider of image capturing device of photogrammetry.
iii)
To access the performance of each control mechanisms.
1.4
Scope
The scope of this project is to design a controller that can be used to control
the speed of a motorized linear actuator that move spontaneously with the conveyer
belt. The efficiency and the performance of the motorized linear actuator with
implementation of control methodology will be assessed. Ac Servo Motor controller
using MR configurator software are the focus of the project.
3
CHAPTER 2
LITERATURE REVIEW
2.1 Research Background
Standard method for complex 3D measurement tasks need to have object with
a high number of object points. Close range photogrammetry offered potential
measurement with convergent multi- image configurations (Luhmann, 2010).
Inspection of incoming parts with no human interface can be done but this required at
the finished assemblies and photogrammetry is usually done when the products is in
static condition. To make it in time inspection at the early stage without stopping the
production line, actuators to run corresponding with the conveyor belt is designed for
the visual inspection. However highly precision position and speed controls are needed
especially in motion control equipment (Rashidi et al., 2015). Types of actuators are
compared of its function and advantages in application. .Furthermore, controller
should have design with load/ friction compensation, disturbance rejection against
parameter variations in addition to accuracy (Rashidi et al., 2015). Basically the
objective of controller is to make system to reach the optimum position.
2.2 Overview of Inspection System
Products quality and delivery reliability are key factors for success in
manufacturing industry (Colledani et al., 2014). Challenge faced such as delivering the
required production rate of high quality products by minimizing resources in terms of
human power and mechanical power (F. Puente Leo, 2006). Usually traditional
4
approach of inspection method uses measurement such as ruler, calipers, and meter
ruler and so on. Therefore manufacturers look for reliable and consistent automated
visual inspection of their products to reduce manual involvement in inspection. Not
only this, labor intensive methods will result in increase of manufacturing lead time
and production cost, as well as significant delay in detecting the defects
(Fundamentals et al., n.d.).
Basically, finish inspection and in-line inspection are the two main inspection
performed by machining industries. Finish inspection can only performed the work at
the end of the machining process in a special quality room where in- line inspection is
performed at the production line (Ayub et al., 2014).
The advantages of in-line inspection are the identification deviations from the
nominal values, detection absence of vital parts of properties and detection products
out of tolerance at the early stage in manufacturing process to prevent from further
machining, handling, assembly, etc. In addition, information on deviations from target
values may be fed back to process (Ayub et al., 2014).
Among those inspection processes, visual inspection is another kind of
inspection approach that mainly deals with surface quality and maximum defect size.
Defects on surfaces, such as cracks, corrosion, damaged part on a component assembly
also part of visual inspection (Li & Gu, 2004). In the meantime, there are quite of areas
visual inspection have extended to. For an example, areas of robot guidance, inspection
of incoming parts or finished assemblies in application of inspection, part
identification, guidance and control (Ayub et al., 2014). Significant advantages of an
optical visual inspection are it can executed very fast with no human interference and
constant, thus 100% monitoring of the production can be achieved (Kosmopoulos &
Varvarigou, 2001). Lest not, direct input of image information into computers is the
development of fully automated photogrammetric measurement (as a part of visual
inspection). This discover been a possibility for quality control which would be benefit
in industrial inspection (Clarke et al., n.d.).
In many successful and diverse applications, photogrammetry can be regarded
as fully accepted 3D measurements tools. Field of industry, biomechanics, chemistry,
5
biology, archeology, architecture, automotive and aerospace engineering, as well as
accident reconstruction have practiced
photogrammetry (Jiang et al., 2008).
According to Satorres Martínez et al., (2009), different types of defects are detected
based on the design of algorithms which are more towards its geometry and
dimensions. Large variety of industrial application areas also apply photogrammetric
system, including;
Automotive manufacturing, for car body deformation measurement, control of
supplier parts, adjustment of tooling and rigs, establishment of control point
networks, crash testing, etc.;
Aerospace industry, for measurement and adjustment of mounting rigs,
antenna measurement, part-to-part alignment, etc.;
Wind energy systems for deformation measurements and production control;
Engineering and construction, for measurement of water dams, tanks, plant
facilities, etc.
2.3 Photogrammetry
By using camera, digital representing of real object in form of point cloud is a
technique of photogrammetry (Daaam, 2010). In other word, reliable information
about the properties of surfaces and objects is able to obtain through photogrammetry
without physical contact with the objects. The name “photogrammetry” is derived
from three Greek words phos or phot which means light, gramma means letter or
something drawn, and metrein is the noun of measure (Schenk, 2005).
Fundamental principle of photogrammetry is triangulation. Used images can
be divided into stereo photogrammetry and single image photogrammetry. “Lines of
sight” can developed from each camera to points of object by overlapping two or more
images from at least two locations and 3D structure of object reconstructed is defined
as stereo photogrammetry. Stereo photogrammetry is excellent to obtain three
dimensional information for the objects from registered images that are two
dimensional which can be done by intersection of these lines of sight mathematically
6
from the three dimensional coordinates of the points of interest (“Geodetic Systems,
Inc,” n.d.). Second type would be monoscopic photogrammetry (also called as single
image photogrammetry) where information of objects is presented by using monoplotting methods (Marinov, 2003).
On the basic, photogrammetry also divided into two categories: aerial and
terrestrial photogrammetry. Images such as topographic maps and land use details
acquired via overhead shots from an aircraft are known as aerial photogrammetry (Fig.
2.1). Terrestrial photogrammetry is further defined as close range photogrammetry
(Fig. 2.2), an approach where camera generally pointing towards the center of the
object with highly convergent camera orientations when the object size and the camera
distance are both less than 100m (Jiang et al., 2008).
Figure 2.1: Aerial photogrammetry.
(Source: Marinov, 2003)
7
Figure 2.2: Close range photogrammetry.
(Source: Marinov, 2003)
2.3.1
Close range Photogrammetry
Close range photogrammetry become technically and economical successful in
the mid-1980s due to its first breakthrough in automated and high accurate 3D
measurements. Large volume objects with high number of object points can be
obtained based on the convergent multi-image configurations, digital comparators and
digital image processing of the scanned imagery as close range photogrammetry
offered the potential of measurement precision to 1: 500,000. By this, performance of
photogrammetry could be become standard method for complex 3D measurement
tasks (Luhmann, 2010).
8
2.3.2
Technical Issues of Photogrammetry
To form an efficient and economic system, number of technical components
required to succeed use of photogrammetry in industry. Therefore, components and
related technical issues summaries as the following list:
Imaging sensor: resolution (number of pixels), acquisition and data transfer
speed, camera stability, synchronization and etc.;
Targeting and illumination: interested object featured, target shape and size,
and measurement volume;
Image configuration: number of camera stations, desired measurement
accuracy, redundancy, robustness, self- calibration ability, and self- control of
orientation and calibration;
Image processing: automation of target recognition and identification, subpixel measurement of target center, multi-image, matching approaches, and
feature tracking;
3D reconstruction: 3D coordinates determination method (e.g. spatial
intersection, bundle adjustment) and error statistics;
Data interfaces: integration into CAD/ CAM environments, machine and data
interfaces and etc.;
Verification of accuracy: reference bodies, reference data, standards and
guidelines and acceptance tests.
Setup of complex tasks is illustrated in above lists for an appropriate design,
operation of close-range industrial photogrammetry systems. Besides, basic camera
concepts, system designs and measurement tasks for industrial photogrammetry also
presented. An overview of recent technology and applications provided rather than
comprehensive coverage due to large variety of applications and system configurations
is discussed (Luhmann, 2010).
9
2.3.3
Photogrammetric Cameras
Cameras with stable interior orientation and high accuracy are demanded to
reduce need of periodic or on-the-job calibration, and technical possibility for
simultaneous camera calibration. Besides the classical ‘metric camera’, rarely few
cameras are mainly for photogrammetry application. However, limitation of ‘metric
camera’ is it only is used in conjunction with the desired accuracy level of camera.
Photogrammetric cameras (Fig. 2.3 and Fig. 2.4) are designed for high- accuracy
industrial metrology. In the meantime, the integrated processors enable 3D
measurements in off-line (1 camera) or on-line (2 camera) mode (Luhmann, 2010).
Figure 2.3: Examples of photogrammetric cameras.
(Source: Luhmann, 2010).
Figure 2.4: Examples of photogrammetric multi- camera systems.
(Source: Luhmann, 2010).
10
2.3.4
SLR Cameras
High- resolution digital SLR cameras with sensors between 10 and 60
Megapixel are designed for fast and simple photogrammetric work because of its range
of exchangeable lenses, high capacity storage devices and powerful batteries.
Somehow, camera calibration is an important step in the complete process chain as
their mechanical stability is usually poor and with changing interior orientation
(Luhmann, 2010). Classical small format (35mm SLR) are offered by companies such
as Nikon, Canon and Sony are mainly used for off-line applications. The two sample
cameras are shown in Fig. 2.5.
Figure 2.5: Examples of digital SLR cameras.
(Source: Luhmann, 2010)
2.3.5
Camera Calibration
Since accuracy is directly related to sensor quality and correct modeling of
interior orientation, camera calibration is an essential of photogrammetric systems in
industrial application (Luhmann, 2010). Somehow, there would be some difficulties
faced in calibration as stated in following cases:
Camera geometry unstable during image acquisition (e.g. gravity effects)
Geometric configuration of images does not allow bundle adjustment with selfcalibration (e.g. due to weak intersection angle or lack of camera rotation)
11
Objects does not provide enough information (e.g. points, distances) for
calibration
Besides, three or more control points as the datum of object can be introduces
as well as introducing shape constraints in photogrammetric orientation (Luhmann,
2010). Otherwise, image-wise of the camera will be calibrated if the mechanical
instability of the camera is worse than the required accuracy level. As long as the
imaging configuration consists of enough well distributed images, the position of
perspective center is usually adjusted for each image while the distortion values are
kept constant for all images as to enhance the accuracy. Furthermore, precision of
camera calibration can be determined from precision of image and object points, or by
standard deviations of camera parameters (Luhmann, 2010).
2.3.6
Accuracy and Verification
Two most important practical considerations are the specified accuracy of an
industrial measurement system and the achieved accuracy within a real project. Final
accuracy figures can be manipulated simply by increasing the number of observations
in many photogrammetric applications. Furthermore, photogrammetric measured
distances are compared to their calibrated nominal length for the accuracy test. Further
developments of high precision industrial close range photogrammetry is challenging
in industrial photogrammetry (Luhmann, 2010).
2.4 Automated Inspection on Moving Conveyor
Nowadays, manufacturing is very high competitive with automation in quality
control processes (Kosmopoulos & Varvarigou, 2001; Leones et al., 2005). This
included on the moving conveyor, some sort of automated visual processing and
classification of items placed are required in many industrial applications. An
overview of the typical setup is shown in Fig. 2.6 which camera located above
conveyer belt which view the items orthographically. Classification of items placed
are done by the item separator that placed before the camera so the incoming items are