The health condition of hydraulic turbines is one of the most critical factors for the operation safety and financial benefits of a hydro power plant. After the massive entrance of intermittent renewable energies, hydropower units have to regulate their output much more frequently for the balancing of the power grid. Under these conditions, the components of the machine have to withstand harsher excitation forces, which are more likely to produce damage and eventual failure in the turbines. To ensure the reliability of these machines, improved condition monitoring techniques are increasingly demanded. In this article, the feasibility of upgrading condition monitoring of Pelton turbines using novel vibration indicators and data-driven techniques is discussed. The new indicators are selected after performing a detailed analysis of the dynamic behavior of the turbine using numerical models and field measurements. After that, factor analysis is carried out in order to assess which are the most informative indicators and to reduce the dimension of the input data. For the validation of the proposed method, monitoring data from an actual Pelton turbine that suffered from an important fatigue failure due to a crack propagation on the buckets have been used. The novel condition indicators as well as classical indicators based on the spectrum and harmonics levels have been obtained while the machine was in good operation, during different stages of damage and after repair. All of these have been used to train an artificial neural network model in order to predict the evolution of the crack until failure occurs. The results show that using the improved monitoring methodology enhances the ability to predict the appearance of damage in comparison to typical condition indicators.

Nowadays, pump-turbine units have to experience multiple start-stops every day to balance the power production and consumption on the grid. During the transient process of turbine start-up, the hydraulic forces applied to the head-cover would change dramatically and induce high-level stresses on the head-cover bolts. As key components of large hydraulic turbine units, the head-cover bolts are subjected to tens of thousands of tonnes of hydraulic excitation force during operation. Special attention should be paid to the design of the head-cover bolts of large hydraulic pump-turbine units because these units have high water heads and high hydraulic excitation forces. Therefore, the safe design of the head-cover bolts is extremely important to maintain the operational safety of the whole unit. This paper investigates the flow-induced stress characteristics of the head-cover bolts during turbine start-up in a large prototype pump-turbine unit. A complete 3D fluid model and a corresponding 3D structural model, including the head-cover bolts of the pump-turbine unit, were created. The fluid–structure coupling method was used to calculate the structural stresses caused by fluid flow during turbine start-up. The pressure files during turbine start-up calculated by the CFD tool were transferred and mapped to the finite element model of the structural components of the pump-turbine unit. Subsequently, the flow-induced stress characteristics of the head-cover bolts were numerically simulated. The simulation results showed that the hydraulic excitation force on the head-cover bolts increased significantly during turbine start-up, and the displacement and the stress distributions of different head-cover bolts were not uniform. The calculation methods and conclusions in this paper can also be applied to evaluate the flow-induced stress characteristics of head-cover bolts for similar hydraulic pump-turbine units.

Crack appearance in the blade is the most common type of fatigue damage in Francis turbines. However, it is sometimes difficult to detect cracks in time using the current monitoring system, even when they are very large. To better monitor cracks, it is imperative to research the effect of a crack on the dynamic behavior of a Francis turbine. In this paper, the dynamic behavior of a Francis turbine runner model with a crack has been researched numerically. The intact numerical model was first validated by the experimental data available. Then, a crack was created at the intersection line between one blade and the crown. The change in dynamic behavior with increasing crack length has been investigated. Crack-induced vibration localization theory has been used to explain the dynamic behavior changes due to the crack. Modal analysis showed that the adopted theory could basically explain the modal behavior change due to the crack. The FFT results of the modal shapes and the localization factors (LF) has been used to explain the forced response changes due to the crack. Based on the above analysis, the challenge of crack monitoring has been analyzed. This research provides some references for more advanced monitoring technologies.