Nowadays, the inevitable intermittency of electrical energy resources such as solar and wind power is compensated through hydropower systems. The hydraulic turbines are not necessarily working at the steady Best Efficiency Point (BEP) condition anymore. They are being used in different off-design and transient operating sequences to stabilize the electrical grid. This includes off-design operation, start/stop, speed no load, load rejection, etc. Such operations cause flow instabilities with pressure fluctuations, load variations, and cavitation, which may deteriorate the machine. In the current project, we will further develop the artificial intelligence state-of-the-art to detect and control undesirable and damaging flow-induced oscillations in an active manner that will lead to the enhancement of turbine lifetime. A well-developed and trained model can not only detect the presence of damaging flow structures, but it can also take optimal decisions to reduce and control such structures.