Editor’s Note: This is the most recent in a series of profiles provided by the Hydro Research Foundation that highlight potential future members of the hydroelectric power industry and their accomplishments.
Seth Gregg has just completed a Masters in Science in Mechanical Engineering at the Colorado School of Mines and is interested in real world applications of machine learning and statistics to intelligent energy systems, as well as prognostics and health management (PHM). Gregg returned to school after a 12-year career working with process controls and vibration analysis. Currently, Gregg and his wife, Christine, live in Denver and enjoy gardening, viticulture, Oenology, teaching and being involved in the local community.
Gregg completed his thesis for his award in July with the support of Dr. John Steele and has been working with Erin Foraker and John Germann at the U.S. Bureau of Reclamation. The title of his thesis is “Feature Selection and Adaptive Threshold for Automated Cavitation Detection in Hydro Turbines”.
From Gregg’s research:
Hydro turbines 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 hydro turbine runners remains as an expensive problem that reduces power production and shortens the life of the turbine. Hydro turbine 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 for comparing and evaluating cavitation detection features as well as a method for creating adaptive cavitation thresholds and automating the cavitation detection process.
Gregg is actively seeking work in the hydropower industry. To connect with Gregg or learn more about the Research Awards Program please email email@example.com or visit the website www.hydrofoundation.org