This webinar describes some of the challenges faced when monitoring a large fleet of wind turbines. Factors such as different turbine and gearbox types, different condition monitoring systems (CMS), geographically dispersed sites and variations in maintenance practice all make the job of a monitoring engineer a difficult task. Romax utilize in-house software called InSight Fleet Monitor to provide condition monitoring services for over 2 GW of assets globally. Using a single software platform enables the CMS engineers to effectively monitor a huge number of wind turbines efficiently. This webinar uses some recent examples and case studies to demonstrate fleet-wide condition monitoring in practice. Examples focus on main bearing and gearbox fault detection and, most importantly for the operator, methods for predicting the remaining useful life or ‘time to repair’ for key components. View this webinar to learn: -How condition monitoring can be effectively rolled out for large, disparate fleets of wind turbines. -Valuable insights from recent examples in the field, particularly relating to gearbox and main bearing faults. -Predicting ‘time to repair’ for major components.

1. Day-to-day Condition
Monitoring For a Large Fleet
of WindTurbines

2. Before We Start
q This webinar will be available at
www.windpowerengineering.com & email
q Q&A at the end of the presentation
q Hashtag for this webinar: #WindWebinar

3. Moderator Presenters
Paul Dvorak
Windpower Engineering
& Development
Sam Wharton
Romax Technology
John Coultate
Romax Technology

4. Day-to-day condition
monitoring for a large fleet
of wind turbines
Dr John Coultate, Head of Monitoring and O&M Consultancy
Dr Samuel Wharton, Condition Monitoring Engineer
February 19th 2015

5. Contents
1. Introduction to Romax Technology
2. ‘Condition Monitoring 101’
3. Challenges faced monitoring a large fleet of wind
turbines
4. Practical examples - main bearing and gearbox fault
detection and workflow

6. • Gearbox and drivetrain specialists
• Established in 1989
• Approx. 250 employees globally,
120 in UK, 12 offices worldwide
• Work in a range of industries
o Automotive, Off-road, Marine,
Aerospace
o Wind energy
Romax Technology

7. Track record in condition monitoring
• Romax has assessed the performance and health of over 5GW of wind turbines
globally
• Romax provides a monitoring service for turbines worldwide, including over 40%
of the UK offshore fleet

8. Monitoring Service Example Project
Centrica
• Three UK offshore wind farms: Lincs, Lynn and Inner Dowsing
• 129 x 3.6 MW turbines
• Vibration monitoring service delivered by Romax using Fleet
Monitor software
• Regular health assessment incorporating SCADA analysis

9. InSight

10. Condition monitoring

11. Condition monitoring 101
• Why install CMS?
• The business case is complex with four main sources of return:
1. Catastrophic failures can be avoided
• CMS catches faults developing and enables more up-tower repairs.
• E.g. High speed shaft and generator bearing faults are reliably detected
before a critical failure occurs. Damaged components are replaced up-
tower without a large crane.
2. Crane costs are minimised by combining operations
• Early detection of faults means that crane operations can be combined
for multiple turbines rather than reacting to one-off failures.

12. Condition monitoring 101
• Why install CMS?
3. Downtime reduced
• Pro-active maintenance - spare parts and crane are
ordered before a failure occurs.
4. Improved annual energy production
• Early detection using CMS means turbines with faults
can be de-rated and run through high wind periods
before scheduled repair.

13. Example return from CMS – main bearing
replacement
• Significant benefits to predicting main bearing failure and scheduling multiple simultaneous
repairs:
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
• Main bearing fault
detected on one 1.5
MW turbine
• Continue running
turbine during windy
season.
• Calculate optimal de-­‐‑
rating if necessary
• Main bearing
fault detected
on another
turbine
• Continue
running both
turbines while
repairs are
scheduled
• Crane and spare
parts are ordered
for 2x turbines
• Repair both
turbines
simultaneously
during low wind
season
Total cost saving for this
single operation ~ $310k
on two turbines
Main sources of ROI:
1. Reduced crane cost
2. Reduced downtime/
increased power production

14. Challenges faced
monitoring a large fleet
of wind turbines

15. CMS (Bently Nevada,
Commtest, SMP, etc.)
Wind farm 1
(e.g. Siemens, Vestas, etc.)
Challenge #1 – Too many different type of wind
turbine and CMS
Wind farm 2 (e.g.
GE, Gamesa, Clipper, etc.)
CMS-­‐‑specific
database and
software
CMS (Gram & Juhl
TCM, B&K Vibro, etc.)
CMS-­‐‑specific
database and
software
• Monitoring
engineers can be
overwhelmed by
different pieces
of software and
data
• Difficult to make
consistent
decisions
• Often lots of
staff requiredMonitoring
engineer(s)

16. CMS (Bently Nevada,
Commtest, SMP, etc.)
Wind farm 1
(e.g. Siemens, Vestas, etc.)
Romax server
‘Hardware independent’ condition monitoring
architecture
Romax monitoring
service
Fleet MonitorTM
software
Wind farm 2 (e.g.
GE, Gamesa, Clipper, etc.)
Database or
site server
Database or
site server
CMS (Gram & Juhl
TCM, B&K Vibro, etc.)

17. Challenge #2 – Keeping track of faults and alarms
from 100s/1000s of turbines
• ‘Workflow’ is a major concern.
• Above a certain fleet size, keeping track of faults and alarms is difficult. Too many
alarms is a problem.
• Concise routine reports with top findings, red/amber/green classifications and
recommendations:

18. Challenge #3 – Effectively incorporating SCADA
analysis and other data
• SCADA analysis is well established for power production reporting; power curve
analysis; wind resource assessment, etc.
• SCADA reporting generally well implemented for NERC compliance
• Not well utilized for reliability analysis

19. Condition monitoring tools
• Good condition monitoring software
should be able to:
o Handle data from multiple CMS vendors.
o Easily switch between different
configurations (multiple gearbox variants,
turbine types, power ratings)
o Provide useful alarms that accurately
indicate fault progression.
o Ideally: Be a portal for allowing operators
and monitoring engineers to keep track
of data from multiple sources to aid fault
diagnosis and maintenance planning.
Insight Fleet MonitorTM Software

20. Condition monitoring tools
Raw Vibration Data
Time
Processing
(FFT..etc)
Component Specific Alarm
Turbine
Drivetrain
Operating
Conditions
Drivetrain
Info +
Experience

21. Condition monitoring tools – Gearbox
Information
• Condition monitoring software needs to have built-in information on every gearbox/drivetrain variant
operating in the fleet.
Gearbox1
Gearbox2
Raw Vibration Data
Time (sec)
Time (sec)
Frequency (Hz)
Frequency (Hz)
Frequency
Transform
(FFT)
Frequency
Transform
(FFT)
Frequency Spectra
Gearbox1
frequency table
Gearbox2
frequency table

22. Condition monitoring tools – Operating
Conditions
• Condition monitoring software needs to have access to the operating conditions of a wind
turbine at the point of time the measurement was taken (i.e. Active Power and Shaft Speeds)
HSS Shaft
at 20 RPM
HSS Shaft
at 25 RPM
All power classes
Near rated power
Peak Amplitude Trending
Amplitude

23. • Fault peak tracking is a very useful technique for detecting the onset of faults, but can often be poor
indicators of advanced damage
• In Fleet Monitor we can easily combine multiple measurements and trends into one more powerful
indicator of fault progression – The Romax Health Index.
Condition monitoring tools- Trending
Combine multiple
parameters
in Fleet Monitor
Romax
Health
Index
Peak
Amplitude
Trending

24. Condition monitoring tools - Alarm Setting
• Two types of alarm threshold:
o Manual – Alarm thresholds are chosen
based on guidelines or experience by
monitoring engineer.
• Don’t require historical data
• Sometimes are not very sensitive
o Automatic – Alarm thresholds are set
based on a fitted distribution to the
data.
• Require historical data
• Can be very sensitive

25. Condition monitoring tools – SCADA data
Vibration
SCADA-­‐‑based
Temperature
Time
Fleet Monitor

26. Practical examples

27. CMS case study 1 – main bearing faults
• Typical main bearing failure modes detected by CMS:
Severe outer race macropiaing and cracking
Roller macropiaing
Severe roller damage
Inner race macropiaing

28. CMS case study 1 – main bearing faults
• Typical main bearing fault development over a long time period:
First Romax Alarm
8.5 months
This turbine had a damaged front main bearing. Indentation marks recorded on rollers and inner race.
Bearing Replaced
Main Bearing Health Index
Date

29. CMS case study 1 – main bearing faults
• Main bearing fault that developed in 30 days:
This turbine had a damaged front main bearing. There were indentation marks on the inner ring.
Romax Alarm
Increased grease
flushing regime to
prolong life
Bearing Replaced
Over 4 months power
production after first
alarm
>4 months
Main Bearing Health Index

30. CMS case study 2 – gear tooth faults
• Typical gear failure modes detected by CMS:
Root bending overstress
Tooth fatigue crack

31. CMS case study 2 – gear tooth faultsGear Health Index
1st CMS Alarm
Turbine Stopped
Turbine started without replacement
Replacement of
High Speed Shaft
4 Hours
2nd CMS Alarm

32. CMS case study 3 – planetary stage
faults
• Typical planetary stage failure modes detected by CMS:
Tooth fatigue crack
Severe roller macropiaing
Planet bearing inner race
macropiaing

33. CMS case study 3 – planetary stage
faults
• Analysis of historical
data:
• Planetary gear stage
failed
catastrophically
• OEM did not detect
the fault
• Romax analysis detected
the fault over 3 months
before failure
Health index
Romax Alarm
>3 months
Turbine with 2nd stage
ring gear fault
Healthy
turbine

34. CMS software case study – HSS bearing fault
• HSS Bearing Yellow (warning) Alarm
triggered by Romax Bearing Health
Index trend.
Alarm triggered

35. CMS software case study – HSS bearing fault
• HSS Bearing Yellow (warning) Alarm
triggered by Romax Bearing Health
Index trend.
• Alarm is investigated by monitoring
engineer using vibration analysis
toolbox.
• Clear fault frequencies associated
with specific HSS bearing fault.
• Report sent to farm operator
recommending inspection and oil
sample analysis in next six months
plus continued monitoring.
Alarm triggered
HSS
Bearing
Fault
Frequency
Harmonic
1
HSS
Bearing
Fault
Frequency
Harmonic
2
Fault frequencies

36. CMS software case study – HSS bearing fault
• Health index trend continues to
increase.
• Inspection carried out by Romax
engineers confirms damage to
bearing.
• Oil analysis shows high Fe content.
• Operator keeps track of reports.
• Operator stores oil analysis results.
• Replacement scheduled.
High Fe

37. CMS software case study – HSS bearing fault
• Bearing health index triggers red
(critical) alarm.
• Exception report sent to operator.

38. CMS software case study – HSS bearing fault
• Bearing health index triggers red
(critical) alarm.
• Exception report sent to operator.
• Replacement carried out
• Maintenance record updated in
Fleet Monitor.
• Post-replacement Health Index
trend drops to new baseline level.
• Alarm threshold to be lowered.

39. Remaining useful life

40. 3y+
2y
1y
Event
Condition
Life Model
Inspect
Vibration
What is a remaining useful life
model?

41. Predictive life models
• For many years, predictive life models have been used for maintenance scheduling:
o Aerospace; power production; helicopters; etc.
• Some pitfalls to avoid:
o You can’t just simply use a model from a different industry for a wind turbine
o You can’t rely on a computer simulation to mimic complex wind turbine failures
• Romax are pioneering a predictive life model approach for wind turbines.

42. Life Model Benefits
• Life models allow effective long term maintenance planning by:
o Ranking components for wear levels over time
o Working in conjunction with existing systems and processes
(CMS, particle counters, inspections)
• A predictive maintenance strategy can greatly reduce future
operating costs

43. Summary and Conclusions

44. Summary and conclusions
• Scaling up a condition monitoring operation poses
some difficult challenges:
o Hardware independent monitoring
o Building an expert team
o ‘Workflow’ – keeping track of faults and alarms
o Predicting failures
• Romax deliver specialist software and services to solve
these problems.

46. Questions?
Paul Dvorak
Windpower Engineering & Development
pdvorak@wtwhmedia.com
Twitter: @windpower_eng
Sam Wharton
Romax Technology
Samuel.wharton@romaxtech.com
John Coultate
Romax Technology
john.coultate@romaxtech.com

47. Thank You
q This webinar will be available at
www.windpowerengineering.com & email
q Tweet with hashtag #WindWebinar
q Connect with Windpower Engineering & Development
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