Prediction of Electromagnetic Characteristics in Stator End Parts of a Turbo-Generator Based on MLP and SVR

Likun Wang, Yutian Sun, Baoquan Kou, Xiaoshuai Bi, Hai Guo, Fabrizio Marignetti and Huibo Zhang
Additional contact information
Likun Wang: Harbin Electric Machinery Company Limited, Harbin 150040, China
Yutian Sun: Harbin Electric Machinery Company Limited, Harbin 150040, China
Baoquan Kou: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Xiaoshuai Bi: National Engineering Research Center of Large Electric Machines and Heat Transfer Technology, Harbin University of Science and Technology, Harbin 150080, China
Hai Guo: The College of Computer Science and Engineering, Dalian Minzu University, Dalian 116600, China
Fabrizio Marignetti: Department of Electrical and Information Engineering, The University of Cassino and South Lazio, 03043 Rome, Italy
Huibo Zhang: Georgia Institute of Technology, College of Engineering, Atlanta, GA 30332, USA

Energies, 2021, vol. 14, issue 18, 1-14

Abstract: In order to study the multiple restricted factors and parameters of the eddy current loss of generator end structures, both the multi-layer perceptron (MLP) and support vector regression (SVR) are used to study and predict the mechanism of the synergistic effect of metal shield conductivity, relative permeability of clamping plates and structural characteristics of eddy current losses. Based on the eddy current losses of generator end structures under different metal shielding thicknesses and electromagnetic properties, the calculation accuracy of the MLP and SVR is compared. The prediction method gives an effective means for the complex design of the end region of the generator, which reduces the effort of the designers. It also promotes the design efficiency of the electrical generator.

Keywords: turbo-generator; eddy current losses; data driven; support vector regression; multi-layer perceptron (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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