Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression

doi:10.1155/2020/4605625

	Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression
	Zhang, Renhui1,2 ; Zhao, Xutao 1
	2020-02-28
发表期刊	MATHEMATICAL PROBLEMS IN ENGINEERING
ISSN	1024-123X
卷号	2020
摘要	The inverse problem is always one of the important issues in the field of fluid machinery for the complex relationship among the blade shape, the hydraulic performance, and the inner flow structure. Based on Bayesian theory of posterior probability obtained from known prior probability, the inverse methods for the centrifugal pump blade based on the single-output Gaussian process regression (SOGPR) and the multioutput Gaussian process regression (MOGPR) were proposed, respectively. The training sample set consists of the blade shape parameters and the distribution of flow parameters. The hyperparameters in the inverse problem models were trained by using the maximum likelihood estimation and the gradient descent algorithm. The blade shape corresponding to the objective blade load can be achieved by the trained inverse problem models. The MH48-12.5 low specific speed centrifugal pump was selected to verify the proposed inverse methods. The reliability and accuracy of both inverse problem models were confirmed and compared by implementing leave-one-out (LOO) cross-validation and extrapolation characteristic analysis. The results show that the blade shapes within the sample space can be reconstructed exactly by both models. The root mean square errors of the MOGPR inverse problem model for the pump blade are generally lower than those of the SOGPR inverse problem model in the LOO cross-validation. The extrapolation characteristic of the MOGPR inverse problem model is better than that of the SOGPR inverse problem model for the correlation between the blade shape parameters can be fully considered by the correlation matrix of the MOGPR model. The proposed inverse methods can efficiently solve the inverse problem of centrifugal pump blade with sufficient accuracy.
关键词	Centrifugal pumps Extrapolation Gaussian distribution Gaussian noise (electronic) Gradient methods Machinery Maximum likelihood estimation Mean square error Reliability analysis
DOI	10.1155/2020/4605625
收录类别	SCI ; SCIE
语种	英语
资助项目	National Key Research and Development Program of China[2016YFB0200901] ; National Natural Science Foundation of China[51979135]
WOS研究方向	Engineering ; Mathematics
WOS类目	Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000522081000007
出版者	HINDAWI LTD
EI入藏号	20201108293656
EI主题词	Inverse problems
EI分类号	618.2 Pumps - 921.6 Numerical Methods - 922 Statistical Methods - 922.2 Mathematical Statistics
来源库	WOS
引用统计	被引频次：7[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/64191
专题	能源与动力工程学院
通讯作者	Zhang, Renhui
作者单位	1.Lanzhou Univ Technol, Sch Energy & Power Engn, Lanzhou 730050, Peoples R China; 2.Lanzhou Univ Technol, Key Lab Fluid Machinery & Syst, Lanzhou 730050, Peoples R China
第一作者单位	能源与动力工程学院; 兰州理工大学
通讯作者单位	能源与动力工程学院; 兰州理工大学
第一作者的第一单位	能源与动力工程学院
推荐引用方式 GB/T 7714	Zhang, Renhui,Zhao, Xutao. Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020.
APA	Zhang, Renhui,&Zhao, Xutao.(2020).Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression.MATHEMATICAL PROBLEMS IN ENGINEERING,2020.
MLA	Zhang, Renhui,et al."Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020).

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