DocumentCode
525706
Title
Artificial neural network based radial bending characteristics of mixed-flow pump impeller
Author
Ruixuan, Jia
Author_Institution
Key Lab. of Condition Monitoring & Control for Power Plant Equip. Minist. of Educ., North China Electr. Power Univ., Beijing, China
fYear
2010
fDate
23-25 June 2010
Firstpage
237
Lastpage
239
Abstract
Impeller radial bending characteristic has applied to many type turbine machines except of pump. Specially, there is no news about application on the mixed-flow pump. In this study, an artificial neural network (ANN) was used for modeling the performance of mixed-flow pump impeller. Thirty seven results were used to train and test. Many patterns have been randomly selected and used as the test date. The main parameters for the experiments are the Gamma, Betal and Beta2. Gamma, Betal and Beta2 have been used as the input layer, and η has been used as the output layer. The best training algorithm and number of neurons were obtained. At last, a new type, high efficiency mixed-flow pump impeller can be designed.
Keywords
Artificial neural networks; Blades; Compressors; Impellers; Laboratories; Numerical simulation; Polynomials; Pumps; Testing; Turbines; artificial neural networkt; mbced-flow pump; radial bending;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on
Conference_Location
Chengdu, China
Print_ISBN
978-1-4244-7324-3
Electronic_ISBN
978-89-88678-22-0
Type
conf
Filename
5542920
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