Inverse Method of Centrifugal Pump Blade Based on Gaussian Process Regression
Zhang, Renhui1,2; Zhao, Xutao1
AbstractThe 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.
KeywordCentrifugal pumps Extrapolation Gaussian distribution Gaussian noise (electronic) Gradient methods Machinery Maximum likelihood estimation Mean square error Reliability analysis
Indexed BySCI ; SCIE
Funding ProjectNational Key Research and Development Program of China[2016YFB0200901] ; National Natural Science Foundation of China[51979135]
WOS Research AreaEngineering ; Mathematics
WOS SubjectEngineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000522081000007
EI Accession Number20201108293656
EI KeywordsInverse problems
EI Classification Number618.2 Pumps - 921.6 Numerical Methods - 922 Statistical Methods - 922.2 Mathematical Statistics
Source libraryWOS
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Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorZhang, Renhui
Affiliation1.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
First Author AffilicationColl Energy & Power Engn;  Lanzhou University of Technology
Corresponding Author AffilicationColl Energy & Power Engn;  Lanzhou University of Technology
First Signature AffilicationColl Energy & Power Engn
Recommended Citation
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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