1) The document discusses Siemens Gamesa's use of visual detection technology like drones and computer vision to inspect wind turbine blades. 2) It outlines Siemens Gamesa's current capabilities for drone inspections, as well as their expectations for drone inspection suppliers to improve technologies. 3) The presentation calls for industry standards around issues like failure mode catalogues, data interchange formats, and image quality metrics to help the technology mature and ensure quality.

1. Visual Detection Technology in
Siemens Gamesa
Wind Power Blades & Beyond
https://goo.gl/rHcgPcRestricted © Siemens Gamesa Renewable Energy 2017

2. Unrestricted © Siemens Gamesa Renewable Energy
2017.10.11Page 2 Allan Moeller Larsen // Service PLM Program Manager
About me
Allan Moeller Larsen | M.Sc. Engineering, Innovation & Business
Program Manager in Service PLM
Responsible for Blade Inspection & Data Analysis Concept: A Visual Detection
Technology
Mobile: +45 2429 5580 | Email: allan.m.larsen@siemens.com
LinkedIn: https://www.linkedin.com/in/larsenallan
Background
• Lives in Vejle and works in Brande, Denmark.
• 2,5 years as Business Startup Consultant for SET
• 5,5 years as project manager in Siemens Wind Power A/S
• IT, Digitalization, Big Data & Analytics

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2017.10.11Page 3 Allan Moeller Larsen // Service PLM Program Manager
Replacing this...
With this..
For that..

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Why are we at TUS Nordics?
Siemens Gamesa = Serious UAV Player!
Your drone = Our drone?

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2017.10.11Page 5 Allan Moeller Larsen // Service PLM Program Manager
Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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2017.10.11Page 6 Allan Moeller Larsen // Service PLM Program Manager
Siemens Gamesa Renewable Energy
Company Size after April 2017 Merger

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2017.10.11Page 7 Allan Moeller Larsen // Service PLM Program Manager
Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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2017.10.11Page 8 Allan Moeller Larsen // Service PLM Program Manager
Condition
Time
Visual Detection of Failure Modes
Blade External Surface
What is it?
Point where failure starts
to occur. Not necessarily
related to age
Point where we can detect
that the products starts to fail
(Potential Failure)
Point where the
product has failed
(Functional Failure)
F
P
Category: Erosion on the leading edge
Degredation: filler layer
What is it not?
P-F Interval
Blade External Surface

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Siemens Gamesa current state
Operational platform for internal use
Drone inspections
Ground based
inspections
Legacy data
Data Annotation

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Offshore Inspections with Drones
Onshore inspections with Drones and Ground Based Systems
Visual Inspections Products
Two main uses – same data source type
Keeping it running
Maintenance & Repair
Kicking Tires
End of Warranty or Asset Trading
Standard analysis product Premium analysis product
Operational todayLive in 2017
Clients
cloud
Soon...

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2017.10.11Page 11 Allan Moeller Larsen // Service PLM Program Manager
Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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Gartner’s Hype Cycle for Emerging Technologies, July 2017
Disappointments
await??

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Blade = Very expensive component
Applied UAV Technology in Siemens Gamesa
The Business Case for Blades funds Technology Maturation
Repair
x 80
VS
Whats next?

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Multiple Supplier Setup
Challenges of conforming a variety of data sources
Inspection DecisionsAnalysis
€ / wtg
Total
One platform
Multiple
suppliers
[...]
Challenges
Performance, Quality &
Technology
Conformity Flexibility
• Current suppliers with operational
readiness approval on drones
and/or Ground Based Systems
Inspection Suppliers

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Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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Quality and Performance
What and how to measure
Image
OverlapMETRICS
Inspection
Speed
Surface
Coverage
? Weather
Dependency
Requirement
Specifications
[...]Image
Quality
Time
Metric
Time
Metric
Time
Metric
Time
Metric
• Accurate
• Stable (precise)
• Inaccurate
• Stable
• Accurate
• Unstable
• Inaccurate
• Unstable
Tolerance
Undesirable

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Poor data examples
...Other than blurry or onfocused images
Missing Surface Coverage Imprecise and inaccurate meta data

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Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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Automated Annotation*
16MP image
Process time: 1,81s
False detection
Quality Price
*Siemens Gamesa Prototype results from July
Demand

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Drone Technology Expectations
From OEM’s and Asset Operators
• Autonomous systems to reduce human error & variation
• Fly using a single rotor position
• Become weather resistant and photograph in difficult
conditions. Weather windows are for maintenance!
Drone Performance
• Fast raw data sharing with client
• Onsite or onboard QA tools
Drone connectivity
• Raw data sharing with full image meta data set and
drone data
• Maintenance system integration
Data openness
AI
IoT
API’s

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Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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Industry Standards Needed
Easy of
• Asset operators and OEM’s will
want to maintain proprietary failure
mode catalogues.
• Assets will be traded and operated
by different parties in their lifetime
• Big data analytics require
normalization
• Navigation of the UAV tech jungle
is hard
• Many say they can do things they
can’t do in real life
• It must be easy to share raw visual
inspection data and meta data sets
• As industry matures, more
operators will want to integrate
failure mode data to computerized
maintenance management
systems
Failure Mode Standards
Autonomous Systems Test &
Validation Standard
Data Interchange Standards
• What kind of image quality is
required for accurate and precise
(consistent) failure mode
detection.
• How can an inspection provider
prove that their image quality is
great?
Image quality standards

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Q&A5
Thoughts on Standards4
Technology3.2
Quality & Operational Performance3.1
Expectations to Drone Inspection Suppliers & Technology Developers3
Our Current Capabilities2
Siemens Gamesa Intro1
Blades & Beyond
Agenda: Visual Detection Technology in Siemens Gamesa

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Questions?

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UAV’s will reduce the cost of Renewable Energy