VISVESVARAYA TECHNOLOGICAL UNIVERSITY

“Jnana Sangama”, Belagavi - 590018, Karnataka, India

Submitted in partial fulfillment of the requirements for the award of the Degree
BACHELOR OF ENGINEERING
In
MECHANICAL ENGINEERING
By

1. Akshay Kumar H V 1DA21ME002

Designation, Department of ME, Dr. AIT, Bengaluru – 560056

DEPARTMENT OF MECHANICAL ENGINEERING,

Dr. AMBEDKAR INSTITUTE OF TECHNOLOGY
MALLATHAHALLI, OUTER RING ROAD, BENGALURU – 560056

2024-25
 Dr. AMBEDKAR INSTITUTE OF TECHNOLOGY
Mallathahalli, Bengaluru – 560056
Department of Mechanical Engineering

Certificate
Certified that the project work entitled “Development of an Autonomous UAV for
Mapping and Non-destructive Testing of Wind Turbine Blades ”, carried out by Akshay Kumar
H V , bearing USN: 1DA21ME002,, Bonafide students of Dr. Ambedkar Institute of Technology,
Bangalore – 560056 in partial fulfillment for the award of Bachelor of Engineering in Mechanical
Engineering of the Visvesvaraya Technological University, Belagavi during the year 2024–2025. It is
certified that all the corrections/suggestions indicated for Internal Assessment have been incorporated
in the Report deposited in the departmental library. The Major project report has been approved as it
satisfies the academic requirements.

Signature of the HOD Signature of the Principal

(Dr. T N Raju) (Dr. M. N. Thippeswamy)

External Viva
Name of the Examiners Signature with Date

1.

2.
 Dr. AMBEDKAR INSTITUTE OF TECHNOLOGY
Mallathahalli, Bengaluru – 560056

Department of Mechanical Engineering

Declaration
We, AKSHAY KUMAR H V, is independently carried out by us at Department of Mechanical
Engineering, Dr. Ambedkar Institute of Technology, Bengaluru-560056, , Department of
Mechanical Engineering, Dr. Ambedkar Institute of Technology. The Project work is carried out in
partial fulfillment of the requirement for the award of degree of Bachelor of Engineering in Mechanical
Engineering during the academic year 2024- 2025.

Place: Bengaluru Name & Signature of students

Date: AKSHAY KUMAR H V

 ACKNOWLEDGEMENT

The satisfaction that accompanies the successful completion of this Major project would be
complete only with the mention of the people who made it possible, whose support rewarded
our effort with success.

We are grateful to Dr. Ambedkar Institute of Technology for its ideals and its inspirations for
having provided us with the facilities that have made this mini project a success.

We are grateful to our Principal Dr. M. N. Thippeswamy, Dr. Ambedkar Institute of

Technology, who gave a continuous support and provided us comfortable environment to
work in.

We would like to express our sincere thanks to Dr. T N Raju, Associate Professor and Head,
Department of Mechanical Engineering, Dr. Ambedkar Institute of Technology for his
support. We pay out profound gratefulness and express our deepest gratitude to our Major
project guide Srinuvasu N, Assistant , Department of Mechanical Engineering for the
suggestions and guidance.

We are thankful to our Major project coordinators Dr. Shivappa H .A, Assistant Professor,
Dept. of Mechanical Engineering ,Dr. Preethi K, Assistant Professor, Dept. of Mechanical
Engineering and S Tejesh,Assistant Professor ,Dept. of Mechanical Engineering for their
advice, supervision and guidance throughout the course of the project.

It is our pleasure to acknowledge the cooperation extended by teaching staff and non- teaching
staff members of Dept. of Mechanical Engineering Engineering, Dr. Ambedkar Institute of
Technology for the encouragement during project work. Finally, it gives immense pleasure to
acknowledge the cooperation extended by family members, friends for the encouragement
during this Project Work.

STUDENTS NAME

AKSHAY KUMAR H V
 ABSTRACT

The wind energy industry is witnessing rapid growth, necessitating innovative and efficient
maintenance solutions to ensure the longevity and performance of wind turbines. This project
presents the development of an autonomous unmanned aerial vehicle (UAV) designed for
comprehensive mapping and nondestructive testing (NDT) of wind turbine blades. The UAV is
equipped with state-of-the-art sensors, including high-resolution cameras, ultrasonic sensors, and
infrared thermography, to detect and analyze structural damages such as cracks, delamination, and
erosion.

The autonomous UAV operates with advanced navigation algorithms, allowing for precise flight
control and positioning around the turbine blades. The integration of artificial intelligence and
machine learning techniques facilitates real-time data processing and damage assessment,
providing immediate feedback on the condition of the blades. The UAV’s ability to autonomously
map and inspect large areas without human intervention significantly enhances the safety and
efficiency of maintenance operations.

Furthermore, this project aims to create a robust and reliable system that can operate in various
weather conditions, ensuring continuous monitoring and timely identification of potential issues.
The implementation of such UAV technology in wind turbine maintenance can lead to substantial
cost savings, reduced downtime, and improved overall performance of wind farms, contributing to
the sustainable growth of renewable energy resources.
 TABLE OF CONTENTS

1. ABSTRACT 5
1.1 INTRODUCTION 7

2. THEORETICAL INFRASTRUCTURE 8

2.1. SimonK 30A 2-3S Brushless ESC For RC Model 8

2.2. Pixhawk PX4 Autopilot 2.4.8 32 Bit Flight Controller 9

2.3. Ublox NEO M8N GPS For APM Flight Controller With Compass 10

2.4. DJI F550 Hexacopter frame 12

2.5. FlySky FS-i6 2.4G 6CH RC Transmitter With FS-iA6B Receiver 13

2.6. Orange 11.1V 4200mAh 35C 3S Lithium Polymer Battery 15

2.7. 1000KV Brushless DC Motor 16

3. LITERATURE REVIEW AND BACKGROUND 19

3.1. Overview of Wind Turbine Blades 19

3.2. Inspection Methods for Wind Turbine Blades 22

3.3. UAVs for Non-Destructive Testing and Inspection 25

4. METHODOLOGY AND WORKING PRINCIPLE 26

5. PROTOTYPE DESIGN AND DEVELOPMENT 31

5.1. Hardware integration and Design 31

5.2. Design Parts 35

5.3. Design Calculations 36

6. EXPERIMENTAL STUDIES 40

6.1. Projected Method and Results 44

7. CONCLUSION 50

REFERENCE 51
INTRODUCTION
Robotic welding is one of the most significant technological innovations in modern
manufacturing. It integrates robotics with traditional welding processes to enhance speed,
precision, safety, and efficiency. Since its inception in the 1960s, robotic welding has become
essential in industries such as automotive, aerospace, shipbuilding, and heavy machinery.

The increasing demand for quality and consistency in welding tasks has fueled the
development of intelligent robotic systems capable of mimicking human expertise .

These systems are now designed not just for repetitive tasks but also to handle more complex
and variable welding operations through integration with vision systems, sensors, and artificial
intelligence. This shift marks a new era in manufacturing where human-robot collaboration is
becoming increasingly prevalen

As global competition pushes industries to increase productivity and reduce manufacturing

costs, robotic welding offers an efficient solution. It is now a central component in Industry
4.0, where automation and data exchange in manufacturing technologies are emphasized.
Robotic welding supports the goals of digital manufacturing by improving traceability,
reducing waste, and enabling predictive maintenance through real-time data collection.

Furthermore, the adoption of robotic welding contributes to environmental sustainability by

minimizing material waste and reducing harmful emissions. As welding often involves
dangerous environments and high temperatures, automating these tasks protects human
workers from potential injuries and long-term health risks.

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2. Evolution of Welding Technology
Welding has a rich history dating back to the Bronze Age. The earliest known welding
examples include gold boxes from that era. During the 19th and 20th centuries, significant
advances occurred:

 1800s: Introduction of acetylene and arc welding. Development of tools using flame
and early electric arcs.
 1900s: Development of metal electrodes, submerged arc welding (SAW), gas tungsten
arc welding (GTAW), and gas metal arc welding (GMAW).
 1950s-2000s: Automation, plasma arc welding (PAW), laser welding, and friction stir
welding (FSW) were introduced and refined.
 2000s–present: Increased adoption of robotic and intelligent welding systems. Smart
sensors and data analytics are now being integrated.

Modern welding is classified into two main categories:

 Fusion welding: Melts base materials to form joints (e.g., arc, MIG, TIG, laser
welding).
 Non-fusion welding: Uses fillers without melting base metals (e.g., brazing, soldering,
friction welding).

These technologies have enabled welding in complex environments such as underwater, in

space, and in high-pressure conditions.

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3. Role of Robotics in Welding
Robotics has transformed welding from a labor-intensive process into an efficient, precise, and
automated manufacturing operation. The role of robotics in welding is multifaceted and
extends beyond automation to encompass improvements in productivity, quality control, and
workplace safety.

Robotics has transformed welding from a labor-intensive process into an efficient, precise, and
automated manufacturing operation. The role of robotics in welding is multifaceted and
extends beyond automation to encompass improvements in productivity, quality control, and
workplace safety.

 Precision and Repeatability: Robots execute welding paths with minimal deviation,
ensuring uniform weld quality across high-volume production runs.
 Speed and Efficiency: Robots operate continuously and at high speed, increasing t
hroughput and reducing cycle times.
 Safety Enhancement: Robotics minimize human exposure to welding fumes, UV
radiation, and extreme heat, improving workplace safety.
 Reduced Material Waste: Robotic systems optimize material usage and minimize
errors that may lead to rework or scrapping.
 Process Integration: Welding robots are often integrated with sensors and vision
systems to perform real-time adjustments, detect joint locations, and verify weld quality.
 Cost Reduction: Although initial investment is high, robotic welding reduces long-term
costs associated with labor, errors, and downtime.
 Increased Flexibility: Robots can be reprogrammed to accommodate design changes or
switch between welding tasks, making them suitable for both high- and low-volume
production.

Automated welding
Rectilinear robots move in line in any of three axes (X, Y, and Z). In addition to linear
movement of the robot along axes there is a wrist attached to the robot to allow rotational
movement. This creates a robotic working zone that is box shaped. Articulating robots utilize
arms and rotating joints. These robots move like a human arm with a revolving wrist at the
end. This creates an irregularly shaped robotic working zone known as the work arc.

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There are many factors that need to be considered when setting up a robotic welding facility.
Robotic welding needs to be engineered differently than manual welding. Some of the
considerations for a robotic welding facility are listed below:

The selected welding programs include start / stop, gas pre flushing, electrode feed and nozzle
flushing. Robots have been used about 15 years to weld complete automotive body assembly
and sub assembly components. In general equipment for automatic arc welding is designed
differently from that used for manual arc welding. Automatic arc welding normally involves
high duty cycles, and the welding equipment must able to operate under those conditions. In
addition, the equipment components must have the necessary features and controls to interface
with the control system. The number of items of any one type to be welded must be high
enough to justify automating the process. If the joints are to be welded on a work piece are
few, straight and easily accessible, a rack automatic gas metal gas welding (GMAW) gun or
gas tungsten arc welding (GTAW) torch may be suitable for key welds. An automatics gun
also can be used in a fixed position or on a curved track for a curved or circular weld such as
joining two pieces of pipes or welding a flat base to a cylindrical shape—a task in which a
work piece can be rotated past the gun. If parts are normally need adjustment to fit together
correctly, or if joints are to be welded, they are too wide or different positions from piece to
piece, automating the procedure will be difficult or impossible. The tabletop size robot is used
to maximum effect- welding work piece is one side of a revolving jig. Each side of jig also
can be revolved to allow access to both sides of work piece. Robots work well for repetitive
tasks

Examples of welding robots

KUKA:Their versatility and flexibility make the KUKA KR 6-2 and KR 16-2 (Figure 3) our
most popular robots. These masterful movers have a payload of 6 or 16 kg and, thanks to their

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design, are ideal for all space-saving, cost-effective system concepts. That’s why they are used
virtually everywhere – both in the automotive components industry and in non-automotive
sectors. With minimized disruptive contours and a streamlined robot wrist design, these high
precision multi-talents offer outstanding accessibility, even in confined spaces. For cleanroom
requirements or environments with a high degree of fouling and high temperatures, the KR
16-2 is also available in the special variants Cleanroom (CR)

FANUC:The FANUC F-200iB (Figure 3) is a six degrees of freedom servo-driven parallel

link robot designed for use in a variety of manufacturing and automotive assembly processes.
The F 200iB is engineered for applications requiring extreme rigidity and exceptional
repeatability in a compact, powerful package [

Panasonic:Panasonic Perform Arc C Series (Figure 4) are dedicated customized robot systems,
made 100% on customer request. Some of the important features of these robots can be
summarized as follows High quality welding with high production rate Torsion-free design
for easy transportation with no programming correction, and for program exchanges

MOTOMAN:Motoman is extending the success of its arc welding robotic arms with the
introduction of the first 7-axis arc welding robot. The flexibility of the VA1400 model (Figure
5) can be used to reduce floor space and achieve higher robot density for increased production.
The unique "elbow" axis of the arm also allows the robot to reach around tall parts or reach
into boxy parts

CLOOS:Due to the modular product design, the new generation of CLOOS QIROX welding
robots (Figure 5) can be optionally equipped with a seventh axis. The off-set axis mounted in
the robot base permits horizontal movement of the robot up to 550 mm. The welding of
complex work pieces is simplified and accelerated thanks to the considerably increased range.
The setting and positioning efforts are considerably reduced because, thanks to the eccentric
movement, the welding head can be much easier moved around corners or into niches, for
example.

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3. Robotics in Different Welding Techniques
Spot welding

Spot welding is widely used among the automotive industries as the efficient joining of metal
sheets . Classify under the resistance welding, spot welding acts by generating heats with use
of a high current, approximately about 1000A – 100,000 A. The welding guns are the main
part of the welding. It comes with 2 different kinds but the important is these guns do similar
function as to make a close loop circuit, connecting the power supply to the weld spot

The current passing through the sheet metals as two guns clamps simultaneously. The high
current provided will cause the surfaces contact with the electrodes tend to melting. After the
energy reach the sufficient level, a weld nugget will start to form. The surfaces, (surfaces
between the sheets where having the highest resistance) are heating the surface to be at solid
liquid temperature and forming a molten weld pool [36]. The weld spot which is so called the
Heat Affected Zone (HAZ) is cooling down via the thermal condition, where the heat is
transferred to the gun which is cooled by cooling water that flows through it. The gun is then
open to complete the process. The advantages of the spot welding are that this method uses an
efficient energy which is supplied by electrical power supply and generates high current
through the generator. This method consume less time for heating the materials. Plus with
time for changeovers of material, this method has less lead time than other method and
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produces high production rates. In addition, spot welding is easy for automation due to the
simple construction and yet it no required of filler materials.

3.2 Arc welding

Another important consideration in improving arc welding robot system is sensing ability.
Sensor that is integrated in the central welding system will convert the information from
parameters involved into quantitative data such as digital signal, voltage and current 18 An
example of automated welding process is the work done by Lima and Bracarens that used
structure for electrode voltage decrement in order to detect temperature change during the
process. As a result, the decided value of arc voltage for the welding process becomes more
accurate. Creating control for right torch angle is also the important factor in ensuring high
quality welding.

The study by Silva et al. has established a parallel structure robot where their axes are
independent to each other. Therefore if any defect happened at particular axis, it would not
influence the other axes, avoiding unnecessary use of high accuracy actuator. Damages will
not spread to other axes, resulting in lower maintenance cost. Previously, some researchers
such as Rubinovitz and Wysk used offline programming system in his experiment that
improves productivity and efficiency of welding process. The total time needed for online

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programming tasks is reduced because the process of defining specific points is eliminated.
The system also lowers the buildup costs of the robot programming system

In welding process, sensor is used for estimating the condition of work piece, followed by transforming the information
to the robotics system for further action. Normally sensor is in form of portable micro-electronic device and play
important role in the whole mechanized system. Park et al. [69] explained about mobile welding robot used for
application in U-type cells. System is equipped with touch sensor to modify the misplaced in positioning and
dimensioning. Nevertheless, the price of the robot is very high and it is also very heavy. Sweet has developed an
application of vision sensor system using general electric P50 as shown in Figure 12. Welding robot produces excellent
results for welding joints with 12mm at 12cm/s welding speed. Kim et al. established a system to calculate the position
and orientation of end effectors. It adjusts 19 controllers’ gains for 6-axis manipulator. The maximum magnitude
frequency goes down by 54%. Luo and Chen developed a seam tracking controller that equipped with laser-based
camera. The system has the capability to calculate the starting welding position and to employ two-point linear
interpolation in order to detect missing seam points.

3.3Friction stir welding (FSW)

In the relatively short time since its invention, the new welding process has found potential
applications in a number of industries including aerospace (military/civilian aircraft, aircraft
parts, fuel tanks, rockets), land transportation (tailored blanks, truck bodies, armor plate
vehicles, wheel rims, engine and chassis cradles, fuel tankers, motorcycle and bicycle frames),
railway (tankers and wagons, container bodies, underground carriages and trams),
shipbuilding and marine (panels for decks, sides, bulkheads and floors, helicopter landing
pads, offshore accommodation, hulls and superstructures, aluminum extrusions), construction
(aluminum bridges, window frames, aluminum pipelines, heat exchangers, facade panels),
electrical (bus bars, electrical connectors, electric motor housings, encapsulation of
electronics), and gas (tanks and cylinders)

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Unlike fusion welding processes, for example arc welding, electron beam welding, and laser
welding, the FSW process takes place in the solid phase below the melting point of the
materials being joined (Figure 13). Advantages that have been cited for the process include the
ability to weld alloys that are difficult to weld by fusion welding processes, excellent
mechanical properties, low distortion and shrinkage, no fume, porosity or spatter (frequently
associated with arc welding), energy efficient, and ability to be used in all positions [73].
Additionally, FSW uses a non-consumable tool, requires no filler wire, or gas shielding, and is
tolerant of thin oxide layers

Industrial robots would be a preferred solution for performing FSW for a number of
reasons, including their widespread use in the automotive industry [87], their ability to
repeatedly follow three-dimensional paths and their low costs. The use of an industrial robot
for FSW could also be a major improvement because many process changes can be
intercepted by a software adaption. The first industrial robots had insufficient stiffness and
since they could not deliver the required down force, they were not suitable to use for FSW.
However, nowadays there are robots with very high payloads of one thousand kilograms and
more which are also very stiff. This makes a breakthrough of robotic FSW

Comparative experiment A comparative experiment has been conducted to validate further the
proposed welding system’s ability to emulate a welder’s skills.

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In this experiment, the system records the welding skills of a novice welder, constructs a skill
library, and then welds new tasks using this library. The experimental procedures are
consistent with those described in Sections 3.3.1 and 3.3.2. For the tests, 3 mm stainless steel
workpieces have been used, along with the same electrode, shielding gas, and wire as listed in
Sec tion 3.3.2. A current of 75 A and a wire feeding rate of 196 mm3/min have been recorded.
Table 5 summarises the torch motion parame ters extracted from the novice welder’s
performance. Compared to a professional welder, the novice’s welding parameters exhibit
greater variability across different basic tasks, reflecting the instability of skill performance.
The novice welder’s travelling speed is relatively slowe

Disadvantages of welding robots

Despite the advantages of using a robotic welder, they also present a few concerns. Robotic
welders are expensive to purchase, which means that an average business cannot afford one.
They require trained personnel to man and program and can often break down or need repair.
Other concerns are that the limited movement of a robotic arm might not allow the robot to
weld all necessary places. This means that a human welder will still have to go in and finish
the job. If the object needing to be welded has been placed incorrectly, the welding robot will
still weld in exactly the same programmed places, so that the welds are "off" or located in the
wrong place. Poor programming can also produce inaccurate results. Robots are also limited

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to only a few types of welding, and many of these take longer to cool or can even weaken
metal if not used properly

Applications Across Industries:

 In the automotive industry, robotic welding is extensively used for assembling car
frames and components using MIG and spot welding.
 In aerospace, robots provide precision in welding thin and high-strength materials like
aluminum and titanium.
 In shipbuilding and construction, robotic welding handles large structures where
consistency and strength are critical.
 Electronics and metal fabrication benefit from micro-welding robots that ensure
accuracy in small components.

Current Research Topics in Robotic Welding

Path/motion planning

Once the programmer has defined all of the seams within the vehicle that are to be welded
they then move onto the next programming task, which relates to planning the motions
required for the robotic cell to correctly carry out the welds. In welding rapid manufacturing
technology, path planning is equally important

Image processing
With the development of the computer vision technology and image processing methods,
numerous welding robots and some automatic welding machines are equipped with
corresponding vision sensors to achieve different welding tasks in severe conditions. A weld
pool image processing algorithm based passive-light-vision has been studied [109]. Firstly,
they have designed a kind of method to directly capture the welding pool images of Gas Metal
Arc Welding (GMAW) by a CCD camera with a narrowband filter. Next, using the median
filter and wavelet transform eliminates noise and keeps the details of the image effectively.
Then, they have proposed to adopt the threshold image segmentation for detecting the welding
pool in the image. The segmentation between the connected components and the noises to
include the welding pool with the spots and the block, have been realized by the method to
mark the connected pixels. Finally, through the operations of pixel-by-column scanning and

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pixel-by-line scanning, the groove centerline and the welding torch centerline can be found
out correctly and the deviations of the seam are also obtained. A structured light image
processing technology was proposed by Yue et al. [110] for a pipeline welding automation
projects and a vision-based pipeline girth-welding robot. I this process, the welding torch can
accurately track the weld and complete the Omni-orientation welding automatically.

Artificial intelligence
With the rapid development of modern automation and artificial intelligence technologies,
their application in welding has become a hot research topic. Recently, there has been a rapid
development in computer technology, which has in turn led to develop the fully robotic
welding system using artificial intelligence technology. However, the robotic welding system
has not been achieved due to difficulties of the mathematical model and sensor technologies.
The possibilities of the fuzzy regression method to predict the bead geometry, such as bead
width, bead height, bead penetration and bead area in the robotic GMA (gas metal arc)
welding process was presented [120]. A well-known method to deal with the problems with a
high degree of fuzziness was used to build the relationship between four process variables and
the four quality 30 characteristics, respectively. Using these models, the proper prediction of
the process variables for obtaining the optimal bead geometry can be determined.

Conclusions
In order to fulfill modern day diversified requirements, significant improvements are needed
for each element of welding robots. Robots must be able to integrate with their environment in
order to produce optimum performance. The ability to present knowledge by using prior
information and newly acquired information is another important element. This would provide
people the combination of ideas they have explored. Most of the robots are designed to
operate with human capability. Otherwise, it will reduce opportunities to be the main player in
the market. People should provide robot with fully autonomous system rather than using panel
to control them. Level of cooperation among robots is also important especially when solving
complicated tasks. Working as a team, each part of the robot should communicate well and
perform given tasks using best possible solutions. Power supply is another issue that should be
included in the discussion. Since the world is turning into sustainable way of living, the
developed system must be aligned with them. Instead of using electricity, manufacturers could
use renewable energy or a closed-loop system which maintain the energy sources. All of the
mentioned elements will contribute to a major change in technology of welding robot

References

1.
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