Dr George Grozev presented a seminar titled "Potential use of drones for infrastructure inspection and survey: as part of the SMART Seminar Series on 27th March 2018. More information: http://www.uoweis.co/event/potential-use-of-drones-for-infrastructure-inspection-and-survey/ Keep updated with future events: http://www.uoweis.co/events/category/smart-infrastructure-facility/

1. Potential use of drones for
infrastructure inspection and survey
Dr. George Grozev, Honorary Senior Fellow
SMART Infrastructure Facility, University of Wollongong
27th of March 2018

2. Outline
•Acknowledgments
•Introduction
•Drone technology
•Risks when using drones
•Rules when flying drones
•Examples of drone applications
for infrastructure inspection
•Conclusion and questions

3. •Pleased to visit SMART Infrastructure Facility and UoW
•Thanks to Prof. Pascal Perez for his support and for
inviting me to present this seminar
• Ms Kate Kofod, Ms Lynda Hezemans, Ms Leanne
Harmison and Tim Davis for their admin and IT help in
relation to my seminar
•Thanks to Mr. Donald Armstrong and Mr. Matt Lawson
from V/Line Pty Ltd for their discussions related to
potential drone application in railway transport
•Thank you to all of you for attending
Acknowledgments

4. Some photos - DJI Mavic Pro

5. More photos - DJI Mavic Pro

6. The remote control of DJI Mavic Pro

7. The remote control connected to
smart devices

8. Components and subsystems
PropellersMotorsBattery
Start button
Autopilot
Power management
Camera
Gimbal
Micro SD cardForward vision sensors
LEDindicator
Radio receiver
GPS/GLONASS
Electronic speed
controller
LED indicator
Elbanhawi M et al (2017). Enabling technologies for autonomous MAV
operations. Progress in Aerospace sciences, 91: 27-52
Wi-Fi
Downward vision sensors

9. Smart phone and iPad-based
applications

10. Aircraft movements
Vertical axis
Longitudinalaxis
Lateral axis
Yawing
Rolling
Pitching

11. Rolling about Longitudinal axis

12. Pitching about Lateral axis

13. Yawing about the vertical axis

14. Quad-rotor propeller configuration
T1 ω1
F1
T2 ω2
F2
T4 ω4
F4
T3 ω3
F3
Fi – Thrust Force of propeller i
Ti – Reactive Moment of propeller i
ωi – angular velocity of propeller i
G – Vehicle weight
G
Adapted from:
Amezquita-Brooks L. et al. (2017). Towards a standard design model for quad-rotors: A review of
current models, their accuracy and a novel simplified model. Progress in Aerospace sciences, 95: 1-23.
Fi = 0.5 ρSCT(kVi)2
S – disk area of the propeller
CT – thrust coefficient of the propeller
ρ – air density
kVi – angular speed of the propeller
motor with voltage Vi

15. Propeller control and UAV movements
ω2
ω4
ω1
ω3
ω2
ω4
ω1
ω3
ω2
ω4
ω1
ω3
ω2
ω4
ω1
ω3
Thrust movement
ω1 = ω2 = ω3 = ω4
Roll movement
ω4 > ω2
ω1 = ω3
Pitch movement
ω1 > ω3
ω2 = ω4
Yaw movement
{ω2 = ω4} > {ω1 = ω3}
Based on: Amezquita-Brooks L. et al. (2017). Towards a standard design model for quad-rotors: A
review of current models, their accuracy and a novel simplified model. Progress in Aerospace
sciences, 95: 1-23.
See also: Máthé K. and Busoniu L. (2015). Vision and control for UAVs: A survey of general methods
and of inexpensive platforms for infrastructure inspection. Sensors, 15:14887-14916.
doi:10.3390/s150714887
Forward direction

16. One drone classification
Drones
UAV μUAV MAV NAV SD
Fixed
wing
Flapping
Wing
VTOL Tilt rotor
Ducted
fan
Helicopter
Orni
copter
Unconven
tional
Bio MAV
Rotary
wing
Mono
copter
Twin
copter
Tricopter
Quad
rotor
Penta
copter
Octo
copter
Deca
copter
Dodeca
copter
Hexa
copter
Based on:
Hassanalian M and Abdelkefi A (2017). Classifications, applications, and design challenges of drones: A review.
Progress in Aerospace Sciences, 91 (2017) 99-131. doi:10.1016/j.paerosci.2017.04.003
PAV

17. A brief comparison of some popular
recreational drones
Drone Name Top Speed Max Flying
Time
Max Flight
Distance
Video Resolution
DJI Phantom 4 Pro 72 km/h (S-mode) 30 min 10 km 4K Ultra HD, 60p
DJI Phantom 4 72 km/h (S-mode) 28 min 10 km 4K Ultra HD, 30p
DJI Mavic Pro 65 km/h (S-mode) 27 min 13 km 4K Ultra HD, 30p
DJI Mavic Air 68.4 km/h (S-mode) 21 min 10 km 4K Ultra HD, 30p
DJI Spark 50 km/h 16 min 5.5 km FHD: 1920×1080 30p

18. Drone Name Mechanical Gimbal Camera Battery
Capacity
Supported SD Remote
Controller
Weight
DJI Phantom 4 Pro 3-axis (pitch, roll, yaw) 20 MP 5870 mAh microSD (up to 128G) Yes 1388 g
DJI Phantom 4 3-axis (pitch, roll, yaw) 12 MP 5350 mAh microSD (up to 64G) Yes 1380 g
DJI Mavic Pro 3-axis (pitch, roll, yaw) 12 MP 3830 mAh microSD (up to 64G) Yes 734 g
DJI Mavic Air 3-axis (tilt, roll, pan) 12 MP 2375 mAh microSD (up to 128G) Yes 430 g
DJI Spark 2-axis (pitch, roll) 12 MP 1480 mAh microSD (up to 64G) Yes 300 g
Weblink
https://www.dji.com/phantom-4-pro/info
https://www.dji.com/phantom-4/info
https://www.dji.com/mavic/info
https://www.dji.com/mavic-air/info
https://www.dji.com/spark/info
A brief comparison of some popular
recreational drones – cont.

19. A brief comparison of some popular
commercial drones
Drone Name Type Dimensions (unfolded) Battery Capacity Number of
batteries
Hovering time Weight
Matrice 600 Pro Hexacopter 1668mm × 1518mm × 727mm4500 mAh (TB47S); 5700 mAh
(TB48S)
6 No payload: 32 min; 6
kg payload: 16 min
9.5 kg (with six
TB47S batteries)
Matrice 200 Quad rotor 887×880×378 mm 4280 mAh (TB50) 2 3.80 kg (TB50)
Matrice 100 Quad rotor Diagonal Wheelbase: 650
mm
4500 mAh (TB47D) 1 or 2 TB48D battery: No
payload: 28 min; 500g
payload: 20 min; 1kg
payload: 16 min
2.431 kg (TB48D)
Drone Name Max Flying
Time
Top Speed Max Service Ceiling Above
Sea Level
Max
Takeoff
Weight
Max Payload Operating
temperature
Weblink
Matrice 600 Pro 65 km/h 2500 m with 2170R propellers;
4500 m with 2195 propellers
15.5 kg 6 kg -10° C to 40° C https://www.dji.com
/matrice600-
pro/info#specs
Matrice 200 38 min, no
payload, TB55;
24 min with full
payload, TB55
82.8 km/h (S-mode) 3000 m 6.14 kg 2.34 kg (TB50) -20° C to 45° C https://www.dji.com
/matrice-200-
series/info#specs
Matrice 100 79.2 km (ATTI mode, no
payload)
3.6 kg 1.245 kg (TB47D) -10° C to 40° C https://www.dji.com
/matrice100/info#spe
cs

20. Risk models of UAVs
There are two main hazards identified when
using drones:
• A collision or near collision between a UAV
and another aircraft (in the air or on the
ground)
• The impact of the UAV or its components with
people or structures on the ground (Ground
Risk Model)

21. Ground risk model
• Failure model
• Impact location model
• Recovery model
• Stress model
• Exposure model
• Incident stress model
• Harm model
Washington A et al. (2017). A review of unmanned aircraft system ground risk models.
Progress in aerospace sciences, 95: 24-44. https://doi.org/10.1016/j.paerosci.2017.10.001

22. Rules when flying drones for
recreational purposes
• You must not fly the drone higher than 120 metres above the
ground
• You must not fly your drone over or near an area affecting public
safety or where emergency operations are underway. Examples
include situations such as a car crash, police operations, a fire and
fire fighting, search and rescue operations
• You must not fly your drone within 30 metres of people, unless the
other person is part of controlling or navigating the drone
• You must fly only one drone at a time
• You must not fly over or above people. This could include festivals,
sporting ovals, populated beaches, parks, busy roads, etc.
• You must not operate your drone in a way that creates a hazard to
another aircraft, person, or property
• You must not operate your drone in prohibited or restricted areas.
Source: CASA
https://www.casa.gov.au/modelaircraft

23. Rules when flying drones for
recreational purposes - continued
• If your drone weighs more than 100 grams:
– You must keep your drone at least 3 nautical miles (5.5 km)
away from controlled aerodromes (usually those with a control
tower)
– You may fly within 3 nautical miles (5.5 km) of a non-controlled
aerodrome or helicopter landing site (HLS) only if manned
aircraft are not operating to or from the aerodrome. If you
become aware of manned aircraft operating to or from the
aerodrome/ HLS, you must manoeuvre away from the aircraft
and land as soon as safely possible.
– You must only fly during the day and keep the drone within
visual line-of sight. This means being able to orientate, navigate
and see the aircraft with your own eyes at all times (rather than
through a device, for example, through goggles or on a video
screen).
Source: CASA 96/17: Direction — operation of certain unmanned aircraft
(https://www.legislation.gov.au/Details/F2017L01370)

24. Licensing for commercial use
• Study Civil Aviation Safety Authority’s (CASA) web site -
www.casa.gov.au/drones
• Get an Aviation Reference Number from CASA
• Excluded “<= 2 kg” category for commercial use
• Remote Pilot License (RePL) - requires one week training and
examination from a certified training organisation
• Aeronautical Radio Operator Certificate
• Remotely Piloted Aircraft Operator Certificate (ReOC) – for a
sole trader or company

25. Battery rules and battery safety
• LIPO – Lithium Polymer Batteries are the preferred batteries for most
light drones
• Regular battery checks for charge level, swelling, leakage and overall
conditions
• Checking battery life
• Use only approved chargers
• Never charge the batteries unattended
• Do not puncture a battery cell
• If you crash your drone and have access to it, carefully remove the
battery from the drone, if possible. Wait and watch the battery for at
least 20 min as a damaged battery could catch fire even when it may
look fine initially.
• Charge the batteries in open and ventilated area on a safe surface.
• Special rules for batteries in your carry on luggage

26. Research challenges/questions
• Risk analysis and risk reduction in drone
applications
• Image processing and image analytics
• Full autonomy and preprogramming the flying path
• Swarm of drones – multi-agent cooperation
• Many others

27. Advantages provided by drone
applications
• High resolution images and video (new digital
capabilities)
• Cheap inspection and access to hard-to-reach
infrastructure elements (cost and access)
• Safer and quicker than dangerous inspections by
humans (safety and efficiency)
• No need to disconnect operations (availability
and reliability)
• Improve and new business processes based on
regular and precise inspection (new
opportunities)

28. Challenges in drone applications
• Difficult to remotely/manually operate in complex
and dynamic environments
• Difficult to operate in all weather conditions
• Autonomy restrictions and difficulties in flight path
planning/mission planning
• Payload and flight duration restrictions
• Communication limitations (range, speed,
bandwidth, interference, etc.)
• Risks from potential collision in the air or impact on
the ground
• Operations Beyond the Visual Line of Sight (BVLOS)
Elbanhawi M et al (2017). Enabling technologies for autonomous MAV operations.
Progress in Aerospace Sciences, 91: 27-52.
https://doi.org/10.1016/j.paerosci.2017.03.002

29. Applications
PWC (Sep, 2017). Clarity from
above: leveraging drone
technologies to secure utilities
systems
• Market of drone power solutions
in the utility sector ~USD 9.46
billion
• Pre-construction and investment
monitoring
• Asset inventory and
maintenance management
(asset dispersion, safety)
• Vegetation management
• Enhancing water quality
monitoring
https://www.pwc.com.au/pdf/clarity-from-above-leveraging-drone-technologies-to-secure-utilities-systems-pwc.pdf
https://www.pwc.pl/en/drone-powered-solutions.html

30. Asset inspection – Example 1
• Melbourne water – spillway, treatment plant carrier
https://utilitymagazine.com.au/aerial-drones-the-future-of-asset-inspection/
• Assessment of Spillway structure for
– Cracking
– Chipping
– Shifting
– Surface degradation
– Weed encroachment

31. Asset inspection – energy utilities
Electricity and gas utilities examples:
http://ulcrobotics.com/services/unmanned-aerial-utility-inspection-services/
Key benefits:
• Improve safety of the workers
• Reduced inspection and patrol cost
• Improve system reliability
• More efficient use of resources
• Access advanced asset data
Some application areas:
• Identify problematic components
• Thermal imaging for hot spots and poor connections
• To guide a rapid response after disasters and outages
• Inspection of hard-to-access areas of electricity networks
• Helping to inform vegetation management
• Mapping and survey for construction projects
Australian utilities had total revenue ~$70 billion in 2016;
~$50 billion – from the electricity sector

32. Asset inspection
• Offshore oil and gas inspection
http://www.asctec.de/en/cyberhawks-offshore-roav-oil-gas-inspection-video/
• Building inspection (building façades, roofs, other surfaces, cracks and
damages after earth quakes, etc.)
• Counting penguins with a drone in Antarctica
https://www.theage.com.au/world/oceania/licence-to-krill-penguin-hot-spot-found-near-
antarctica-20180306-p4z30y.html
• Hazard identification in disasters
Leizer GKK and Tokody D (2017). Radiofrequency identification by using drones in railway
accidents and disaster situations. Interdisciplinary Description of Complex Systems 15(2):
114-132.
Máthé K. and Busoniu L. (2015). Vision and control for UAVs: A survey of general
methods and of inexpensive platforms for infrastructure inspection. Sensors,
15:14887-14916. doi:10.3390/s150714887

33. Summary and conclusion
• Drone technology is developing very fast, creating a range
of new application opportunities
• Many challenges related to the technology capabilities,
risks, regulation (or lack of) and human control
• Emerging commercial applications for inspection and
survey of infrastructure systems, power and utilities:
– Cost-effective solutions
– Replacing dangerous work by humans
– Increasing availability of infrastructure systems
– High quality images and video, including life streaming and
monitoring
– Variety of cameras, different purpose payload and sensors can
be used

34. Thank you
George Grozev
ggrozev@uow.edu.au
SMART Infrastructure Facility
University of Wollongong