SAMM 2020: Learning Models from Data

Data-based Approach for Fault Diagnosis of Hydropower Rotors

30 Jul 2020, 13:00

1h

Poster Posters 3

Speaker

Mr Christian Sperber (Voith Hydro Holding GmbH & Co. KG)

Description

The poster presents a novel approach to diagnose rotordynamic faults like unbalance and coupling misalignment from measured vibration. For that purpose, a large database of virtual hydropower rotors and their vibration has been calculated. The goal is to create a data-driven diagnosis system from this database, that will be applicable to a variety of real hydropower rotors. In a first step, a gradient boosting regression algorithm has been applied to the database with some preprocessing and showed promising results that now shall be improved in accuracy.

Presentation materials

Poster_csperber_SAMM2020.pdf