The Prediction Method on the Early Failure of Hydropower Units Based on Gaussian Process Regression Driven by Monitoring Data

The Prediction Method on the Early Failure of Hydropower Units Based on Gaussian Process Regression Driven by Monitoring Data

<b> </b>The hydropower units have a complex structure, complicated and changing working conditions, complexity and a diversity of faults. Effectively evaluating the healthy operation status and accurately predicting the failure for the hydropower units using the real-time monitoring data...

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Bibliographic Details
Main Authors: Huade Huang, Aisong Qin, Hanling Mao, Jiahe Fu, Zhenfeng Huang, Yi Yang, Xinxin Li, He Huang
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Applied Sciences
Subjects:
hydropower units
multi-dimensional monitoring information
correlation analysis
Mahalanobis distance
gaussian process regression model
state evaluation
Online Access:https://www.mdpi.com/2076-3417/11/1/153

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