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Finding Useful Features in Vibration Signals for Fault Diagnosis
Author(s) -
Sperber Christian,
Weber Wilhelm,
Eberhard Peter
Publication year - 2021
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.202000023
Subject(s) - fault (geology) , vibration , selection (genetic algorithm) , computer science , hydropower , coupling (piping) , control theory (sociology) , artificial intelligence , pattern recognition (psychology) , engineering , acoustics , physics , geology , mechanical engineering , seismology , electrical engineering , control (management)
This contribution presents a selection of characteristic values derived from vibration signals that are useful for diagnosis of unbalance and coupling bend in hydropower rotors. The characteristic values are used with machine learning techniques for the estimation of fault type as well as fault intensity.