A Practical Approach to the Use of SCADA Data for ...
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A Practical Approach to the Use of SCADA Data for Optimised Wind Turbine Condition Based Maintenance Presenter Christopher Gray Co-authors Klaus Haselgruber Franz Langmayr Simon Watson
Transcript of A Practical Approach to the Use of SCADA Data for ...
A Practical Approach to the Use of SCADA Data for
Optimised Wind Turbine Condition Based Maintenance
Presenter
Christopher Gray
Co-authors
Klaus Haselgruber
Franz Langmayr
Simon Watson
Motivation
Failure Mode Assessment
SCADA Data Analysis
System Response
Physics of Failure
Workflow
Summary
Contents
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Motivation
Significant contribution from several systems, range of failure modes
Monitoring system required to assess overall turbine health status
Specialized CMS for each system not financially viable
SCADA data readily available, high level of detail in modern turbines
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Source: EWEC 2010 “Methodology and Results of the Reliawind Reliability Field Study“
Failure Mode Assessment
System analysis identify failure root causes, damage drivers and model parameters
Expert input to identify key issues
Input for model development & fault diagnostic algorithms link to available data
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Limitations of SCADA 10-minute Logs
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Information loss for dynamic signals (Nyquist theorem) missing features
Non-linear damage kinetics, error in remaining life estimates
Improvement: on-line analysis, improve data aggregation
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Log N
Lo
g S
Shock Loads
S-N Curve (simplified example)
Signal Noise
Blade Pitch Activity
10-min log 10-min log ….
SCADA Data Analysis: Quick Wins
Large number of turbines, large data volumes automated analysis and statements
High data quality required, check for errors (sensors, signal form, drift, cross checks)
System health check simple analysis techniques (statistics, correlations, trends)
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Early Warning of Overheating, Turbine 4
System Response Modelling & Monitoring
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Library of models for various systems, as analysed in Failure Mode Assessment
On-line comparison of measured vs expected behaviour
Yaw Operation
Pitch Operation
Gbox Oil Temperature
Generator Winding
Power Performance
Rotor Aerodynamics
Bearing Temperatures Part load, elevated temperature
Controller alarm limit
Early warning
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Prognostics, Physics of Failure
SCADA log defines load history for various systems and components
Models created to describe the relationship between load and damage accumulation
Transfer functions generated where damage driver is not directly measured
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Generator Winding Thermal Aging
Gearbox Bearing High Cycle Fatigue
Rotor Blade Laminate De-bonding
Drive Shaft Flange Fretting
Yaw Drive Ring Gear Adhesive Wear
Pitch Motor Housing High Cycle Fatigue
Foundation High Cycle Fatigue
Damage driving events
99.9%
99.9%
Gearbox Temperature Residual [°C]
Active
Po
we
r R
esid
ua
l [k
W]
Statistics, Reporting, Actions
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PH
YS
ICS
S
TA
TIS
TIC
S
SO
FT
WA
RE
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Statistics, Reporting, Actions
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ALARMS
Response anomaly
Performance deficit
High failure probability
ACTIONS
Turbine Inspection
Spare parts order
Maintenance schedule
DIAGNOSIS
Expert system
Failure mode identification
Feedback
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Windpark: Demo 1
Date From: 01.08.2010
Date To: 31.08.2010
Conclusions
Holistic, complete life cycle approach required for WEC reliability
SCADA data analysis a valuable & cost effective technique for condition monitoring
Keys to Success
Automated data validation, analysis, reporting
Comprehensive all components and relevant failure modes
Independent all WEC types
Scalable single monitoring solution
Effective integration into asset management program
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Thank You!
