Diagnostic Method for Hydropower Plant Condition-based Maintenance combining Autoencoder with Clustering Algorithms

Author:

Jad S.,Desforges X.,Villard P.Y.,Caussidéry C.,Medjaher K.

Publisher

Elsevier BV

Reference28 articles.

1. 2022 Hydropower Status Report Sector trends and insights (9; p. 47). (2022). International Hydropower Association. https://www.hydropower.org/publications/2022-hydropower-status-report

2. Hydroacoustic interaction between draft tube and penstock eigenmodes under Francis turbine full load instability;Alligné;IOP Conference Series: Earth and Environmental Science,2022

3. Atamuradov, V., Medjaher, K., Dersin, P., Lamoureux, B., & Zerhouni, N. (2017). Prognostics and Health Management for Maintenance Practitioners-Review, Implementation and Tools Evaluation. International Journal of Prognostics and Health Management, 8, 31.

4. A new methodology for hydro-abrasive erosion tests simulating penstock erosive flow;Aumelas;IOP Conference Series: Earth and Environmental Science,2016

5. Barbosa de Santis, R., Silveira Gontijo, T., & Azevedo Costa, M. (2021). Condition-based maintenance in hydroelectric plants: A systematic literature review. 236, 631–646.

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