Symmetrical Loss of Excitation Fault Diagnosis in an Asynchronized High-Voltage Generator

Yanling Lv, Yuting Gao, Jian Zhang, Chenmin Deng and Shiqiang Hou
Additional contact information
Yanling Lv: School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China
Yuting Gao: School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China
Jian Zhang: State Grid Heilongjiang Electric Power Company Limited Electric Power Research Institute, Harbin 150030, China
Chenmin Deng: School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China
Shiqiang Hou: School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China

Energies, 2018, vol. 11, issue 11, 1-18

Abstract: As a new type of generator, an asynchronized high-voltage generator has the characteristics of an asynchronous generator and high voltage generator. The effect of the loss of an excitation fault for an asynchronized high-voltage generator and its fault diagnosis technique are still in the research stage. Firstly, a finite element model of the asynchronized high-voltage generator considering the field-circuit-movement coupling is established. Secondly, the three phase short-circuit loss of excitation fault, three phase open-circuit loss of excitation fault, and three phase short-circuit fault on the stator side are analyzed by the simulation method that is applied abroad at present. The fault phenomenon under the stator three phase short-circuit fault is similar to that under the three phase short-circuit loss of excitation. Then, a symmetrical loss of the excitation fault diagnosis system based on wavelet packet analysis and the Back Propagation neural network (BP neural network) is established. At last, we confirm that this system can eliminate the interference of the stator three phase short-circuit fault, accurately diagnose the symmetrical loss of the excitation fault, and judge the type of symmetrical loss of the excitation fault. It saves time to find the fault cause and improves the stability of system operation.

Keywords: asynchronized high-voltage generator; loss of excitation; fault diagnosis; wavelet packet and BP neural network (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/11/3054/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/11/3054/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:11:p:3054-:d:181038

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().