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Mixed‐flow pump is a typical pump using in low‐head cases of water lifting. The flow field pulsation is usually an important issue in the operation of mixed‐flow pumps and their pumping statins. Due to its large size, it is difficult to monitor the internal flow characteristics well, based on computational fluid dynamics, we use 5678 monitoring points which arranged in the impeller and fixed vane with using the high pulsation tracking network, and the pressure pulsation signals are analyzed by fast Fourier transform and variable mode decomposition to decompose the main frequency and intensity of the pressure pulsation signals, then analyze the energy dissipation with the entropy production rate (EPR). It is found that there are strong low‐frequency (0.416, 0.625, and 1.67 Hz) pressure pulsation near hub, and the pressure pulsation on the shroud is stronger than that on the hub (at least three times or more); there are strong and stable pressure pulsation (25 Hz) on the shroud generated by the rotor–stator interference (RSI); and the EPR in the flow field can be well combined with the signal. Reasonably allocating material strength and controlling the number of vanes and impellers to avoid producing a common multiple can avoid pressure pulsation caused by RSI and reduce energy dissipation. Therefore, it is very effective in improving the efficiency of this part. Under low flow conditions, the siphon outflow passage can predict the high‐frequency (45.833 Hz) attenuation area well through the phase signal decomposition of the signal, which has certain significance for improving its stability and efficiency. [ABSTRACT FROM AUTHOR]

The rotor blades of an axial‐flow turbine are cantilever structures, and there is inevitably a gap between them and the casing. Due to factors such as rotor wear and unit vibration, the eccentricity of the impeller will change during the operation of the turbine, resulting in the impeller being affected by additional radial forces, which can even lead to rubbing or biting between the impeller and the casing. To monitor the eccentricity of the impeller and the additional radial forces in real time during the operation of the turbine, this study conducted numerical simulations of the internal flow of the turbine under different eccentricities of the impeller, and analyzed the characteristics of pressure pulsation and impeller radial force in the turbine using the variational mode decomposition method. The results showed that there was a good linear relationship between the eccentricity of the impeller and the amplitude of the frequency corresponding to the rotor in pressure pulsation at the monitoring point and the Alford force acting on the impeller. Based on this finding, we established mathematical formulas for the relationship between the pressure pulsation at the monitoring point and the eccentricity of the impeller, as well as the eccentricity of the impeller and the Alford force acting on it. According to these formulas, we only need to monitor the pressure pulsation during the operation of the turbine to realize the real‐time monitoring of the eccentricity of the impeller and the Alford force, which is of great significance for ensuring the safe and stable operation of the turbine. [ABSTRACT FROM AUTHOR]

The reversible pump‐turbine plays an important role in hydropower stations, but pressure pulsation during their operation affects their performance and lifespan. Accurate prediction of pressure pulsation signals can provide an important basis for energy planning and stable operation of pumped storage units, thereby promoting sustainable development of the environment. This study introduces an optimization method that combines long short‐term memory (LSTM) and variable mode decomposition (VMD) to enhance the prediction accuracy of pressure pulsation signals. First, by decomposing the pressure pulsation signal into multiple relatively stable subsequence components using VMD, the characteristics of the original signal become more distinct. Subsequently, individual LSTM‐based time series prediction models were constructed for each modal function, and the hyperparameters related to subsequence were optimized using the sparrow search algorithm. To validate the efficacy of the proposed approach, this paper conducted experiments using pressure pulsation signals of a pump‐turbine obtained through numerical simulation. The experimental data was divided into training and testing sets, with the former used to train the LSTM model and the latter used for validation. The experimental results show that the optimized VMD with an optimized LSTM method can effectively improve the prediction accuracy of pressure pulsation signals in reversible pump‐turbine. [ABSTRACT FROM AUTHOR]

In this study, an analysis of a low-specific-speed pump is carried out based on the methods of one-way and two-way fluid–structure interactions (FSIs). This study analyzes the influence of FSIs on the internal flow field and external characteristics of the pump. Utilizing a two-way FSI, the signal coherence analysis method is employed to analyze the coherence of signals between the flow field and the structural field. Addressing the issue of a lack of a connection between the two signals, this study bridges a gap in the existing research. The results indicate that different interaction methods have certain influences on impeller stress and deformation. However, in both coupling modes, the maximum deformation and the maximum equivalent stress have the same distribution position. The head error obtained using the two-way coupling method is lower than that of the uncoupled results, which indicates that the two-way FSI calculation results are closer to the experimental results. The pressure pulsation signals at the interface of the impeller and volute exhibit strong coherence with the structural field signals. For low-specific-speed centrifugal pumps, establishing a clear connection between the flow field signals and structural field signals will help guide further optimization of their performance through design. [ABSTRACT FROM AUTHOR]