LAPSE:2023.19549
Published Article
LAPSE:2023.19549
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, Huibo Zhang
March 9, 2023
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
data driven, eddy current losses, multi-layer perceptron, support vector regression, turbo-generator
Suggested Citation
Wang L, Sun Y, Kou B, Bi X, Guo H, Marignetti F, Zhang H. Prediction of Electromagnetic Characteristics in Stator End Parts of a Turbo-Generator Based on MLP and SVR. (2023). LAPSE:2023.19549
Author Affiliations
Wang L: Harbin Electric Machinery Company Limited, Harbin 150040, China
Sun Y: Harbin Electric Machinery Company Limited, Harbin 150040, China
Kou B: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Bi X: National Engineering Research Center of Large Electric Machines and Heat Transfer Technology, Harbin University of Science and Technology, Harbin 150080, China
Guo H: The College of Computer Science and Engineering, Dalian Minzu University, Dalian 116600, China [ORCID]
Marignetti F: Department of Electrical and Information Engineering, The University of Cassino and South Lazio, 03043 Rome, Italy [ORCID]
Zhang H: Georgia Institute of Technology, College of Engineering, Atlanta, GA 30332, USA
Journal Name
Energies
Volume
14
Issue
18
First Page
5908
Year
2021
Publication Date
2021-09-17
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14185908, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.19549
This Record
External Link

https://doi.org/10.3390/en14185908
Publisher Version
Download
Files
Mar 9, 2023
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
207
Version History
[v1] (Original Submission)
Mar 9, 2023
 
Verified by curator on
Mar 9, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.19549
 
Record Owner
Auto Uploader for LAPSE
Links to Related Works
Directly Related to This Work
Publisher Version