Wind Turbine Fault Diagnosis and Predictive Maintenance Through Statistical Process Control and Machine Learning

Wind Turbine Fault Diagnosis and Predictive Maintenance Through Statistical Process Control and Machine Learning

This study applies statistical process control and machine learning techniques to diagnose wind turbine faults and predict maintenance needs by analyzing 2.8 million sensor data collected from 31 wind turbines from 2015 to 2017 in Taiwan. Unlike previous studies that only relied on historical wind t...

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Bibliographic Details
Main Authors: Jyh-Yih Hsu, Yi-Fu Wang, Kuan-Cheng Lin, Mu-Yen Chen, Jenneille Hwai-Yuan Hsu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Decision trees
fault diagnosis
machine learning
predictive maintenance
random forest
statistical process control
Online Access:https://ieeexplore.ieee.org/document/8966331/

Internet

https://ieeexplore.ieee.org/document/8966331/

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