Incorporating Machine Learning into Vibration Detection for Wind Turbines
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...
Saved in:
Main Author: | J. Vives |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2022-01-01
|
Series: | Modelling and Simulation in Engineering |
Online Access: | http://dx.doi.org/10.1155/2022/6572298 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Machine learning boosts wind turbine efficiency with smart failure detection and strategic placement
by: Sekar Kidambi Raju, et al.
Published: (2025-01-01) -
A machine learning approach for wind turbine power forecasting for maintenance planning
by: Hariom Dhungana
Published: (2025-01-01) -
Forecasting power generation of wind turbine with real-time data using machine learning algorithms
by: Asiye Bilgili, et al.
Published: (2024-12-01) -
VIBRATION MEASUREMENT METHOD OF WIND TURBINE BLADE BASED ON BINOCULAR PHOTOGRAM METRY
by: YAKUP AhMat, et al.
Published: (2020-01-01) -
Wind turbine blade damage detection based on acoustic signals
by: Chenchen Yang, et al.
Published: (2025-01-01)