Exploratory Analysis of SCADA Data from Wind Turbines Using the K-Means Clustering Algorithm for Predictive Maintenance Purposes

Exploratory Analysis of SCADA Data from Wind Turbines Using the K-Means Clustering Algorithm for Predictive Maintenance Purposes

Product maintenance costs throughout the product’s lifetime can account for between 30–60% of total operating costs, making it necessary to implement maintenance strategies. This problem not only affects the economy but is also related to the impact on the environment, since breakdowns are also resp...

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Bibliographic Details
Main Authors: Pablo Cosa Rodriguez, Pere Marti-Puig, Cesar F. Caiafa, Moisès Serra-Serra, Jordi Cusidó, Jordi Solé-Casals
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Machines
Subjects:
predictive maintenance
prognosis
machine learning
K-means
clustering
SCADA data
Online Access:https://www.mdpi.com/2075-1702/11/2/270

Internet

https://www.mdpi.com/2075-1702/11/2/270

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