Flow theory in the side chambers of the radial pumps: A review

Adu-Poku, Kofi Asamoah; Appiah, Desmond

doi:10.1063/5.0006843

Cited by 14 publications

(2 citation statements)

References 96 publications

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“…Pump is considered as one kind of significant and widely-used machine, and mechanical failure caused by pump in machinery system is counted as around over half the proportion [106], [107]. Owing to the defections of fault diagnosis traditional methods discussed above, it is very challengeable and meaningful to exploit the intelligent diagnosis strategies of pump [108]- [111].…”

Section: Cnn-based Fault Diagnosis For Pumpmentioning

confidence: 99%

Convolutional Neural Network in Intelligent Fault Diagnosis Toward Rotatory Machinery

2020

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Rotating machinery is of vital importance in the field of engineering, including aviation and navigation. Its failure will lead to severe loss to personnel safety and the stability of the equipment system. It is a long way to investigate the relevant fault diagnosis method, especially the intelligent fault diagnosis method on the basis of deep learning. In consideration of the limitations of traditional fault diagnosis approaches based on shallow layer network structure, the methods based on deep neural network (DNN) are worthy of thorough exploration. As a common DNN with special structure, deep convolutional neural network is of great concern in intelligent fault diagnosis due to its advantages in processing nonlinear problems. This review will play an emphasis on convolutional neural network (CNN). The basic structure and principle are introduced. The applications of CNN-based fault diagnosis method in rotating machinery are summarized and analyzed. Furthermore, the diagnosis performance and potential mechanism from different CNN methods are discussed. In the end, this review is highlighted on the challenges and the potential key points in research on novel intelligent fault diagnosis strategies. The corresponding analysis and discussion will provide some references and lay the foundation for the investigation in related fields. INDEX TERMS Deep learning, convolutional neural network, intelligent fault diagnosis, rotating machinery.

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Section: Cnn-based Fault Diagnosis For Pumpmentioning

confidence: 99%

Convolutional Neural Network in Intelligent Fault Diagnosis Toward Rotatory Machinery

2020

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“…The electromagnetic (EM) pump is an indispensable equipment for transporting conductive fluids in diverse energy conversion systems, such as liquid metal-cooled nuclear reactors, aerospace, metal casting, and chip heat dissipation [1][2][3]. Compared with the mechanical pumps, the advantages of the EM pump are of contactless drive, no-moving parts, leakage free, and low vibration and noise [4,5]. It is quite suitable in the application in which high reliability and long-life service within extremely harsh conditions are required.…”

Section: Introductionmentioning

confidence: 99%

Active Flow Control of the Magnetohydrodynamic Flow in an Annular Linear Induction Pump by Modifying the Driving Electromagnetic Field

Wang,

Zhang

et al. 2024

International Journal of Energy Research

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The strong coupling between fluid and electromagnetic field in the annular linear induction pump (ALIP) can gradually amplify small disturbance in the fluid field into large-scale vortices. The appearance of the vortices seriously affects the efficiency and reliability of the pump. An active flow control method based on the modification of the driving electromagnetic field is proposed to improve the flow stability. A simplified numerical model of the ALIP is established to simulate the three-dimensional flow in the annular flow channel, and the internal electromagnetic field is modified by using the modulated surface current. The influences of the active flow control method on the flow behavior, pressure pulsation, and energy conversion are, respectively, investigated based on the simulation results. The results show that the modulated surface current can accelerate the vortical evolution. The size and strength of the vortices are suppressed in the modified electromagnetic field. The pressure pulsation low frequency at the ALIP’s outlet is significantly reduced when the modulated surface current density reaches a certain level. The surges in the processes of energy conversion become more gentle within the control method, and the overall energy efficiency is slightly reduced even at the highest modulated surface current density.

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Numerical study of the magnetohydrodynamic flow instability and its effect on energy conversion in the annular linear induction pump

et al. 2021

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A numerical model of annular linear induction pump with a full-scale pump channel is created to study the scale-dependent instability of the magnetohydrodynamic flow. The magnetic-fluid coupling effect is implemented by modifying the underlying governing equations and constraints. The model authenticity is validated by comparing the simulated pressure difference, as well as the pressure pulsation, with the previous experimental data. The flow patterns at different flow rates corresponding to different magnetic Reynolds numbers are depicted from both the azimuthal and meridian viewpoints, and the periodicity of the occurring vortex flows is found in the pump. By analyzing the different mechanisms contributing to the fluid kinetic energy, it is found the competition between the axial components of the Lorentz force and pressure gradient dominates the flow evolution in the pump channel. The magnetic-fluid coupling effect is found to amplify the disturbances in either the magnetic field or the fluid field. It is even effective within the uniform externally imposed magnetic field and inlet velocity only if a disturbance exists in the initial flow. Increase in the cycle number of disturbance can enhance the flow stability and induce smaller vortex flows. Finally, different mechanisms of energy conversion in the pump are analyzed and it is found that the sudden occurrence of vortex flows can induce large current density, which significantly increases the Ohmic dissipation and decreases the efficiency of energy conversion from magnetic field into the fluid. The relatively large Ohmic dissipation in the fluid is the main reason for the low efficiency of such a device.

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Flow theory in the side chambers of the radial pumps: A review

Cited by 14 publications

References 96 publications

Convolutional Neural Network in Intelligent Fault Diagnosis Toward Rotatory Machinery

Convolutional Neural Network in Intelligent Fault Diagnosis Toward Rotatory Machinery

Active Flow Control of the Magnetohydrodynamic Flow in an Annular Linear Induction Pump by Modifying the Driving Electromagnetic Field

Numerical study of the magnetohydrodynamic flow instability and its effect on energy conversion in the annular linear induction pump

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