World Class Wind Turbine Maintenance
Operational excellence dankzij Condition Based Maintenance
Kamperland 27 Mei 2014
Twan Kohlen CEO Oliveira International Group
Data – Informatie - Kennis
Doelstelling
 Ontwikkelen en uittesten integrale control room voor het optimaliseren van
O&M (technisch, organisatorisch en economisch)
 Merkonafhankelijk, generiek meetsysteem, met een open, onafhankelijke
architectuur
 Low cost 10% - 20% huidige CBM systemen met veel meer functionaliteit
 Geen analyzers maar smartphone’s en tablets
 Onafhankelijk windturbine cluster dat klanten kan ontzorgen op het gebied
van O&M
 Voorspelbaar maken van operationele performance, onderhoud, levensduur
en opbrengsten
 Windturbines met ‘bestaansrecht’, los van subsidies
Eindresultaat in modelvorm
Dashboard
Monitoring
Reports
Alerts
Analytical Predictive
Model
Workbench Modeling Management
Engineering Maintenance Intelligence
Business Rules & Processes
SCADA data
Maintenance Records
Process & Asset
Data (origin, options, etc.)
Historian Data
Error logs
Financial/Risk Data
Reliability
Reliabilit
Information
y
Store
Informati
on
Store
Operator Data & Complaints
Inspection Records
Technician/Engineer Data
Condition Monitoring data
Data combineren in ėėn systeem
12 verschilllende systemen en 200+ data ingangen
Klimaat data
Windsnelheid, luchtdruk, relatieve
vochtigheid, windrichting, temperatuur
etc
Proces data
druk, temperatuur, vermogen, snelheid,
belasting, bladhoekverstelling etc
OEM data
tekeningen, onderhoudsadviezen,
logistieke voorraad, gebruiksadviezen,
modificatie standaard, etc
Onderhoud en storingen data
aantal storingen, stilstand tijd, planning
onderhoud, modificaties, MTBF etc
Manuele (gedigitaliseerde) data
CBM data
gehoor, visuele inspectie, lekkage,
scheuren, verkleuring, etc
trillingen, ultrasound, infrarood, olie
kwaliteit, resonanties, corrosie etc
Inventarisatie problemen en wensen
3G/4G – ethernet – satelliet
data
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Ijsafzetting turbine bladen
Tandwielkast schade
Scheurvorming turbine bladen
Towerbending
Resonaties en structuur schade
Gevolgen bliksem inslag
Voorspellen van onderhoud
Logistieke gevolgen van onderhoud
Availability vs productivitie
Turbine rendement absoluut
Weer voorspelling vs productie
…. Etc….
Data intelligentie
Stella Kapodistria
Stella Kapodistria
Condition Based Maintenance
Algorithms
CAMPI project
Goal of the project: to develop service strategies that minimize cost whilst
maximizing the availability and safety of assets.
Maintenance & logistics planning
WP I: Data Pooling, Eindhoven University of Technology
WP II: Maintenance Clustering, Groningen University
WP III: Integration and Implementation, Tilburg University
Funding: Companies 26%, Universities 26%, Dinalog 48%
WP I: Data Pooling,
Eindhoven University of Technology
Pooling of data means statistical analysis using multiple data sources
related to multiple populations.
There are three fundamental objectives:
 Aggregation in order to obtain more precise estimates.
 Comparisons of trends and differences across populations and
times.
 Common interpretation of statistical information from multiple
sources (similar or different populations).
Taxonomy
Data Pooling: Taxonomy
Intra pooling
(a.k.a. sensor fusion)
Different sensor
readings on the
same
asset/component
Inter pooling
Similar sensor
readings on different,
but comparable,
assets/components
Data Pooling
Dynamic mind map
with literature links
Literature overview
paper
Projects with Oliveira
Projects with Oliveira
Data monitoring,
fault detection
and diagnostics
Out-of-control
action plan
(OPAC)
Estimation
of the time to
failure
Estimation of the
initial state of a
wind turbine
Industrial testbed for applying methods from the literature
Improve Oliveira procedures
Projects with Oliveira
Current status:
 data collection
 data analysis (OMIS workstation)
 control charts (X-bar charts)
 identification of trends
 diagnose a possible failure
Data monitoring,
fault detection
and diagnostics
Intra pooling
Goal: Multivariate Statistical Process Control
 joint control charts
 derivation of tighter, joint thresholds
 business economic aspects of MSPC
Projects with Oliveira
Current status:
 Expertise
 Monitoring (OMIS workstation)
Out-of-control
action plan
(OPAC)
Goal: creation of a flowchart for the out-of-control action
plan
 activators
 checkpoints
 terminators
Projects with Oliveira
Goal:
 Identification of critical failures
Estimation
of the time to
failure
 Analysis of failure data
 Analysis of propagated failures
 Derivation of failure time distribution
Projects with Oliveira
Current status:
“Every wind turbine is unique”
Goal:
Estimation of the
initial state of a
wind turbine
 Identification of comparable components
 Creation of in-control indices
 Creation of a flowchart
 Structured algorithmic approach
Projects with Oliveira
Data monitoring,
fault detection
and diagnostics
Out-of-control
action plan
(OPAC)
Estimation
of the time to
failure
Estimation of the
initial state of a
wind turbine
Industrial testbed for applying methods from the literature
Improve Oliveira procedures
Stella Kapodistria
Condition Based Maintenance
Thank you very much!
Questions?
Algorithms