Skip to main navigation
Skip to search
Skip to main content
Teesside University's Research Portal Home
Search content at Teesside University's Research Portal
Home
Profiles
Research units
TeesRep
Student theses
Projects
Datasets
Equipment
Press/Media
Data-Driven Predictive Maintenance of Wind Turbine Based on SCADA Data
Wisdom Udo
, Yar Muhammad
Centre for Digital Innovation
Department of Computing & Games
Research output
:
Contribution to journal
›
Article
›
peer-review
2057
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Data-Driven Predictive Maintenance of Wind Turbine Based on SCADA Data'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Wind Turbine
100%
Supervisory Control
100%
Data-driven Predictive Maintenance
100%
Acquisition Data
100%
Maintenance Cost
25%
Predictive Maintenance
25%
Offshore Wind
25%
Electricity Cost
12%
Characteristic Behavior
12%
Wind Farm
12%
Detecting Anomalies
12%
Operation Cost
12%
Operational Reliability
12%
Sensor Networks
12%
Maintenance Requirement
12%
Data Acquisition System
12%
Offshore Wind Farm
12%
G20 Countries
12%
Long Short-term Memory
12%
Production Output
12%
Wind Power Capacity
12%
International Renewable Energy Agency (IRENA)
12%
Gearbox
12%
Anomalous Behavior
12%
Output Optimization
12%
Statistical Process Control
12%
Extreme Gradient Boosting(XGBoost)
12%
Wind Turbine Components
12%
Engineering
Predictive Maintenance
100%
Supervisory Control
100%
Compressed Air Motors
100%
Data Collection
100%
Applicability
10%
Operation and Maintenance Cost
10%
Long Short-Term Memory
10%
Offshore Wind Farms
10%
Form Part
10%
Turbine Components
10%
Gearbox
10%
Supervisory Control and Data Acquisition System
10%
Statistical Process Control
10%
Chemical Engineering
Process Control
100%
Long Short-Term Memory
100%