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A Diagnostic and Predictive Framework for Wind Turbine Drive Train Monitoring
Martin Bach-Andersen
Department of Applied Mathematics and Computer Science
Cognitive Systems
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Ph.D. thesis
2423
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Computer Science
Data Stream
100%
Focused Research
50%
Collected Data
50%
Deep Learning
50%
Processing System
50%
Fault Detection
50%
Predictive Model
50%
Keyphrases
Train Monitoring
100%
Feature System
33%
Deep Learning Architectures
33%
Complex Vibration
33%
Nonlinear Model Predictive Approach
33%
Sensor Data Streams
33%
Unsupervised Anomaly Detection
33%
Engineering
Wind Turbine
100%
Data Stream
40%
Collected Data
20%
Alarm System
20%
Processing System
20%
Sensor Data
20%
Human Expert
20%
Engineering
20%
Deep Learning
20%
Medicine and Dentistry
Diagnosis
100%
Health Care Cost
50%
Chemical Engineering
Deep Learning
100%