Advanced condition monitoring of Pelton turbines

•The procedure used to improved condition monitoring in Pelton turbines is described.•The vibrations measured during 25 years of monitoring of this type of turbines are analyzed.•Some types of damage found during these years are introduced and discussed.•A numerical model based on FEM reproducing the machine dynamics has been built-up.•The effect of jet misalignment is studied with the model and compared with field-data. The ability of hydropower to adapt the electricity generation to the demand is necessary to integrate wind and solar energy into the electrical grid. Nowadays, hydropower turbines are required to work under harsher operating conditions and an advanced condition monitoring to detect damage is crucial. In this paper the methodology to improve the condition monitoring of Pelton turbines is presented. First, the field data obtained from the vibration monitoring of 28 different Pelton turbines over 25 years has been studied. The main types of damage found were due to fatigue, cavitation and silt erosion. By analyzing the vibration signatures before and after maintenance tasks, the symptoms of damage detected from the measuring locations were determined for each case. Second, a theoretical model using numerical methods (FEM) was created in order to simulate the dynamic behavior of the turbine. The model was validated with the results obtained from on-site tests that were carried out in an existing turbine. The deformations and the stresses of the runner under different operating conditions could then be computed. The calibrated model was used to analyze in detail the effect of misalignment between nozzle and runner. In historic cases, this abnormal operating condition lead to severe damage in the turbine, due to the effect of fatigue in some locations of the buckets. The model reproduced well the symptoms detected in the field measurements. The stresses could be calculated, which eventually can be used to estimate the remaining useful life of the turbine.