Cavitation Aggressiveness Estimation in Hydro Turbines Based on Cyclostationary Modeling

Abstract

This work proposes a new methodology of detection and identification of erosive cavitation in hydro turbines, which is based on cyclostationary modeling of the cavitation induced vibrational signals. Different cavitation types cause damage to different turbine parts and induce different vibrational signatures, which can be employed to identify and locate the cavitation. Additionally, the cavitation aggressiveness can be estimated using the measured power of vibrational signal. High frequency accelerometers picked up the signals from two real turbines under normal operation. The methodology was implemented in software and a specific hardware was developed to run the software locally. Signals were synthesized in accord with the cyclostationary modeling and employed to validate the proposed methodology. Results obtained from real signals were similar to the ones obtained from synthetic signals, and corroborate the feasibility of this methodology in cavitation monitoring systems.