Feature selection and adaptive threshold for automated cavitation detection in hydroturbines
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Hydroturbines produce 6.3% of all electrical generation and 48% of renewable energy in the United States of America. While hydro power plants have existed for well over 100 years, cavitation damage on hydroturbine runners remains as an expensive problem that reduces power production and shortens the life of the turbine. Hydroturbine operators who wish to perform cavitation detection and collect intensity data for estimating the remaining useful life (RUL) of the turbine runner face several practical challenges related to long term cavitation detection. This thesis presents both a method ...