Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow

Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow

The efficiency decline of Francis turbines, a key component of hydroelectric power generation, presents a multifaceted challenge influenced by interconnected factors such as water quality, incidence angle, erosion, and runner wear. This paper is structured into two main sections to address these iss...

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Bibliographic Details
Main Authors: Álvaro Ospina, Ever Herrera Ríos, Jaime Jaramillo, Camilo A. Franco, Esteban A. Taborda, Farid B. Cortes
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
dimensionless analysis
machine learning
prediction
water quality impact
Online Access:https://www.mdpi.com/1996-1073/18/15/4023
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