Vortex pumps play a crucial role in industrial and municipal settings by transferring high-viscosity and particle-laden fluids. However, their performance and reliability are significantly compromised by cavitation. Identifying and diagnosing cavitation promptly is essential for maintaining the proper operation of vortex pumps. The use of current signals as a non-invasive monitoring method has shown great promise in detecting multi-cavitation states. The proposed method integrates dual-tree complex wavelet transform with variational mode decomposition to decompose current signals into multiple modes. Subsequently, the Bayesian optimized locally weighted K-nearest neighbor algorithm is employed to accurately identify multi-cavitation states. High-speed photography is also utilized to observe the incipient, developing, and collapsing phases of cavitation. The results indicate that the proposed method achieves a detection accuracy of 96.67% at a flow rate of 40 m³/h, outperforming other flow conditions. The recognition accuracy reaches 98.33% under stable flow conditions, while accuracies of 92.33% and 93.67% are observed for flow rates of 35 m³/h and 45 m³/h, respectively. The overall average recognition rate across all tested flow conditions is 94.22%. This methodology not only demonstrates high effectiveness in identifying cavitation states but also offers a reliable and practical solution for fault diagnosis in fluid mechanical systems. It significantly contributes to the improvement of operational efficiency, reliability, and maintenance strategies in industrial and municipal pumping systems.

Cavitation-induced flow instabilities in vortex pumps critically degrade hydraulic performance and operational lifespan. This study investigates the evolution of the vapor cavities within vortex pumps across various cavitation states using both numerical simulations and experimental analysis. The unsteady flow dynamics within the impeller channel are examined, and the relationships among pressure pulsations, vortex volume, and vapor volume fraction are analyzed. As cavitation intensifies, the vapor volume expands progressively. Notably, the time required for the vapor to expand during critical cavitation is twice as long as that for severe cavitation, whereas the contraction time is one-fourth. The variation in vortex volume inside the impeller follows a distinct pattern, initially increasing and then decreasing, with the peak occurring during critical cavitation. The interactions between pressure pulsations, vapor volume fraction, and vortex volume become increasingly complex, especially during severe cavitation, where the amplitude of pressure pulsations significantly decreases, the vapor volume fraction increases, and vortex volume fluctuations are suppressed. Wavelet coherence analysis reveals the coupling dynamics of these three variables across different temporal scales and frequency bands, with enhanced coherence observed in the low-frequency range (0–50 Hz). These findings provide valuable insights for the optimization and development of vortex pumps in municipal and industrial fluid transport applications.

The cavitation of the tip leakage vortex (TLV) induced by tip leakage has always been a difficult problem faced by turbomachinery, and its flow structure is complex and diverse. How to accurately extract the main structures that affect the cavitating flow of the TLV from the two-phase flow field is a key problem. In this study, the main mode extraction and low order mode reconstruction accuracy of the cavitation flow field of TLV downstream of National Advisory Committee for Aeronautics (NACA)0009 hydrofoil by two dynamic mode decomposition (DMD) methods are compared. The research shows that the main modes extracted by the standard DMD method contain a large number of noise modes, while the sparsity-promoting DMD eliminates the noise modes, showing obvious advantages in the reconstruction accuracy of the velocity field. The characteristics of cavitation signals are analyzed, and the cavitation signals are divided into four categories, which explains the reason why DMD methods have low reconstruction accuracy in cavitation. This study provides a theoretical basis and strong guarantee for the extraction of mode decomposition characteristics of the two-phase flow field. This is of great significance for accelerating the prediction of multiphase flow fields based on intelligent flow pattern learning in the future. Meanwhile, it also provides a new method and road for the introduction of artificial intelligence technology in future scientific research.

The finite-time Lyapunov exponent (FTLE) method is a mature and practical method for analyzing the characteristics of Lagrangian coherent structures. It can be used for studying the severe impacts of cavitation on the coherent structure of flow. The reduced-order modeling (ROM) method has also significant advantages in extract key features of flow structure. This study analyzed the cloud cavitation flow structure of National Advisory Committee for Aeronautics (NACA)0015 hydrofoil. The backward FTLE and ROM were combined, and a comparison was made between the low-order modes of FTLE structure and the FTLE obtained from the low-order modes. The results indicate that the two methods have effectively captured the main coherent structural features of cloud cavitation flow fields. The main characteristic structures captured by the FTLE obtained from the low-order modes of the flow field are much clearer. The first two coherent structures of the FTLE obtained from the low-order modes of the flow field decompose the FTLE of the velocity field into three distinct parts: the leading-edge structure of the hydrofoil, the reflux structure in the middle of the hydrofoil, and the wake region of the hydrofoil. It is proved that the combination of FTLE and ROM can provide a new perspective and means for the analysis of turbulent structures.

A novel multi-objective optimization design approach is presented integrating the Improved Whale Optimization Algorithm (IWOA) with Back Propagation Neural Network (BPNN) for the centrifugal pump with vaned diffuser. The primary objectives of this optimization are to enhance pump efficiency and reduce pressure pulsation. Under head constraints, seven critical geometric design variables of the vaned diffuser centrifugal pump were identified as optimization parameters. Sample data were generated using Latin Hypercube Sampling (LHS) to construct a high-accuracy surrogate model, which was subsequently globally optimized using IWOA. The optimization results were validated through numerical simulations, revealing that the optimized model achieves a 1.56% increase in efficiency and a 28.6% reduction in pressure pulsation intensity. These enhancements significantly improve the operational stability and reliability of the pump. Furthermore, the research delves into entropy production analysis and the comparison of unsteady flow characteristics, elucidating the mechanisms behind the reductions in internal energy losses and the improvements in flow field properties resulting from the optimized design. This work provides a novel methodology for designing high-efficiency, low-vibration centrifugal pumps, offering substantial engineering application value and valuable theoretical insights.

Tubular turbine is a type of turbine with low-head. Due to the fact that the runner of a tubular turbine is of axial-flow type, there will be a certain width of blade tip between the blade and the chamber. In order to explore the influence of tip clearance width on the flow inside the turbine, taking the model tubular turbine as the research object, six different tip clearance widths were compared and analyzed. The research shows that the increase in blade tip clearance width affects the performance of the turbine, reduces the minimum pressure at blade tip and causes cavitation in advance. Larger tip clearance width significantly increases pressure pulsation intensity inside the turbine, especially in the vaneless region between the runner and guide vane and the area of the runner tip. However, the increase in tip clearance width can greatly reduce the axial force for about 100 N and radial excitation force for about 50% of rotating parts. Therefore, during the design and processing of tubular turbines, the blade tip clearance width should be carefully selected to ensure safe and stable operation of the unit.