The hump characteristic is one of the main problems for the stable operation of pump turbines in pump mode.However,traditional methods cannot reflect directly the energy dissipation in the hump region.In this paper,3D...The hump characteristic is one of the main problems for the stable operation of pump turbines in pump mode.However,traditional methods cannot reflect directly the energy dissipation in the hump region.In this paper,3D simulations are carried out using the SST k-ω turbulence model in pump mode under different guide vane openings.The numerical results agree with the experimental data.The entropy production theory is introduced to determine the flow losses in the whole passage,based on the numerical simulation.The variation of entropy production under different guide vane openings is presented.The results show that entropy production appears to be a wave,with peaks under different guide vane openings,which correspond to wave troughs in the external characteristic curves.Entropy production mainly happens in the runner,guide vanes and stay vanes for a pump turbine in pump mode.Finally,entropy production rate distribution in the runner,guide vanes and stay vanes is analyzed for four points under the 18 mm guide vane opening in the hump region.The analysis indicates that the losses of the runner and guide vanes lead to hump characteristics.In addition,the losses mainly occur in the runner inlet near the band and on the suction surface of the blades.In the guide vanes and stay vanes,the losses come from pressure surface of the guide vanes and the wake effects of the vanes.A new insight-entropy production analysis is carried out in this paper in order to find the causes of hump characteristics in a pump turbine,and it could provide some basic theoretical guidance for the loss analysis of hydraulic machinery.展开更多
A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectivel...A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.展开更多
基金Supported by National Key Technology R&G Program(Grant No.2012BAF03B01-X)Innovative Research Groups of National Natural Science Foundation of China(Grant No.51121004)
文摘The hump characteristic is one of the main problems for the stable operation of pump turbines in pump mode.However,traditional methods cannot reflect directly the energy dissipation in the hump region.In this paper,3D simulations are carried out using the SST k-ω turbulence model in pump mode under different guide vane openings.The numerical results agree with the experimental data.The entropy production theory is introduced to determine the flow losses in the whole passage,based on the numerical simulation.The variation of entropy production under different guide vane openings is presented.The results show that entropy production appears to be a wave,with peaks under different guide vane openings,which correspond to wave troughs in the external characteristic curves.Entropy production mainly happens in the runner,guide vanes and stay vanes for a pump turbine in pump mode.Finally,entropy production rate distribution in the runner,guide vanes and stay vanes is analyzed for four points under the 18 mm guide vane opening in the hump region.The analysis indicates that the losses of the runner and guide vanes lead to hump characteristics.In addition,the losses mainly occur in the runner inlet near the band and on the suction surface of the blades.In the guide vanes and stay vanes,the losses come from pressure surface of the guide vanes and the wake effects of the vanes.A new insight-entropy production analysis is carried out in this paper in order to find the causes of hump characteristics in a pump turbine,and it could provide some basic theoretical guidance for the loss analysis of hydraulic machinery.
基金Sci-Tech Planning Projects of Chongqing City,China(No.CSTC2007AA7003).
文摘A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.
