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DNV GL © 2017 23 June 2017 SAFER, SMARTER, GREENER DNV GL © 2017
23 June 2017
Robots Change the Game
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Drones and Submersibles as Disruptors in Renewables
Asset Management: An Offshore Wind Application
Elizabeth Traiger Ph.D. M.Sc.
DNV GL © 2017 23 June 2017
UK Wind Power Generation
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Credit: Carbon Brief, renewableUK
15.7 Gigawatts installed capacity
– Onshore
– 10.4 GW
– 1226 operational projects
– Offshore
– 5.3 GW
– 28 operational projects
– Leader since October 2008
7,600+ wind turbines
8.7% for the grid on 22 June 2017
DNV GL © 2017 23 June 2017
Present O & M Loop
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SCADA Data Asset
Management Solution
Inspection and
Maintenance
Wind Turbine
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Offshore Wind Turbine Asset Inspections Today
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Blade Inspections
Impacts to turbine performance
– Cracking
– Erosion
– Lightning strike
– Delamination
– General damage
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Substructure
Monitor
– Corrosion
– Marine growth
– Cable burial
– J-tube integrity,
– Scour protection monitoring
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The Future: Robotic Multi-Vehicle Autonomous Solution
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Unmanned Aerial Vehicle
Performance:
– Visual RGB inspections
– Multispectral inspection
– Lidar scanning
State of the art
– Autonomous flight
– Relative localization
– Environmental tolerances
Next Challenges
– Legislation of operational limits
– Integration with USV
– Automated power management
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DNV GL © 2017 23 June 2017
Unmanned Surface Vehicle
Performance:
– Transfer to turbine
– Secure and Deploy UAV and UUV
State of the art:
– Autonomous navigation
– Sensing and positioning
Next Challenges:
– Deployment system for UUV and UAV
– Power management
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DNV GL © 2017 23 June 2017
Unmanned Underwater Vehicle
Performance:
– Visual RGB inspections
– Sonar inspection
State of the art
– Remotely Piloted
– Multi-sensor deployment
– Relative localization
Next Challenges
– Autonomous operation
– Deployment from USV
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Onshore Autonomous Flight
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Automated Fault Detection
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Part Distance from hub
Side of Structure
Fault Type Fault Size
Blade B 1.5m LE Crack 0.17m long
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Turbine Inspection Method Comparison
Rope Access
Ground Camera
Helicopter Manual UAV
Automated UAV
Time 2-3 hours 2-3 hours 2 hour 20 min 15 min
Data Quality ~1 mm/px ~10 mm/px ~10 mm/px ~10 mm/px 1 mm/px
Data Consistency Low Medium Low Medium High
Personnel 3-4 2-3 3 2-3 1
Risk to Personnel High Medium Medium Low None
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Impact on O&M
Consistent inspection database
Increased inspection speed
Increased quantity of information an asset
Higher quality of data
Preventative maintenance strategies
Reduced H&S risks
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DNV GL © 2017 23 June 2017
Challenges
Autonomous multi-system collaboration
– Positioning
Robotic vehicle deployment
Data path to asset management
Regulation on autonomous systems
– Pace of regulation development versus pace of technology development
– Visual line of sight
– System supervision requirements
– Spatial constraints
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DNV GL © 2017 23 June 2017
SAFER, SMARTER, GREENER
www.dnvgl.com
Thank you
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Elizabeth Traiger, Ph.D., M.Sc. [email protected]
Drone Video and input from Perceptual Robotics [email protected]