Affiliation:
1. Institute of Automatic and Industrial Informatics, Universitat Politècnica de València, Valencia 46022, Spain
Abstract
With machine learning techniques, wind turbine components can be detected and diagnosed in advance, so degeneration can be prevented. Automatic and autonomous learning is used to predict, detect, and diagnose electrical and mechanical failures in wind turbines. Based on the implementation of machine learning algorithms adapted to the different components and faults of wind turbines, this study evaluates different methodologies for monitoring, supervision, and fault diagnosis.
Subject
Computer Science Applications,General Engineering,Modeling and Simulation
Cited by
2 articles.
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