Resumen
One of the main causes of damage in hydraulic turbines is cavitation. While not all cavitation appearing in a turbine is of a destructive type, erosive cavitation can severely affect the structure, thus increasing maintenance costs and reducing the remaining useful life of the machine. Of all types of cavitation, the maximum erosion occurs when clouds of bubbles collapse on the runner surface (cloud cavitation). When this occurs it is associated with a substantial increase in noise, and vibrations that are propagated everywhere throughout the machine. The generation of these cavitation clouds may occur naturally or it may be the response to a periodic pressure fluctuation, like the rotor/stator interaction in a hydraulic turbine. Erosive bubble cavitation generates high-frequency vibrations that are modulated by the shedding frequency. Therefore, the methods for the detection of erosive cavitation in hydraulic turbines are based on the measurement and demodulation of high-frequency vibrations. In this paper, the feasibility of detecting erosive cavitation in hydraulic turbines is investigated experimentally in a rotating disk system, which represents a simplified hydraulic turbine structure. The test rig used consists of a rotating disk submerged in a tank of water and confined with nearby axial and radial rigid surfaces. The excitation patterns produced by cloud cavitation are reproduced with a PZT (piezoelectric patch) located on the disk. These patterns include pseudo-random excitations of different frequency bands modulated by one low carrier frequency, which model the erosive cavitation characteristics. Different types of sensors have been placed in the stationary and in the rotating parts (accelerometers, acoustic emission (AE), and a microphone) in order to detect the excitation pattern. The results obtained for all the sensors tested have been compared in detail for the different excitation patterns applied to the disk. With this information, the best location and type of sensor to detect the different excitations have been identified. This study permits improving the actual technique of detecting erosive cavitation in hydraulic turbines and, therefore, to avoid operation under these circumstances.