An advanced machine learning framework for cavitation detection in hydro plants

To ensure the efficient operation of hydro plants, there is an increasing focus on predictive maintenance techniques, which enable early detection of failures and wear in equipment components. This paper presents the development of an advanced machine-learning framework for the detection of cavitation in hydro turbines. By detecting cavitation early, failure can be averted, downtime minimized and overall productivity maximized.