Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation

Chao Wang, Xiao Liu, Zhe Chen

Research output: Contribution to journalJournal articleResearchpeer-review

19 Citations (Scopus)

Abstract

Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree of insulation degradation of one turn in the winding of a PMSWG. Cosimulation method by combining finite element model and external circuits is used. Hilbert–Huang transformation is applied to detect the very early stage fault in interturn insulation by analyzing the stator current. Detection results show that the minimum detectable severity degree of interturn fault in this paper is 0.1488%, which is much better than the best record in the literature.
Original languageEnglish
Article number8206504
JournalI E E E Transactions on Magnetics
Volume50
Issue number11
Number of pages4
ISSN0018-9464
DOIs
Publication statusPublished - Nov 2014

Fingerprint

Fault detection
Stators
Permanent magnets
Insulation
Degradation
Networks (circuits)

Keywords

  • Fault detection
  • Hilbert–Huang transformation (HHT)
  • Interturn insulation fault
  • Permanent magnet synchronous wind generator (PMSWG)

Cite this

@article{af99a8e1101046d2b4ae1933647a982d,
title = "Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation",
abstract = "Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree of insulation degradation of one turn in the winding of a PMSWG. Cosimulation method by combining finite element model and external circuits is used. Hilbert–Huang transformation is applied to detect the very early stage fault in interturn insulation by analyzing the stator current. Detection results show that the minimum detectable severity degree of interturn fault in this paper is 0.1488{\%}, which is much better than the best record in the literature.",
keywords = "Fault detection, Hilbert–Huang transformation (HHT), Interturn insulation fault, Permanent magnet synchronous wind generator (PMSWG)",
author = "Chao Wang and Xiao Liu and Zhe Chen",
year = "2014",
month = "11",
doi = "10.1109/TMAG.2014.2318207",
language = "English",
volume = "50",
journal = "I E E E Transactions on Magnetics",
issn = "0018-9464",
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Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation. / Wang, Chao; Liu, Xiao; Chen, Zhe.

In: I E E E Transactions on Magnetics, Vol. 50, No. 11, 8206504, 11.2014.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation

AU - Wang, Chao

AU - Liu, Xiao

AU - Chen, Zhe

PY - 2014/11

Y1 - 2014/11

N2 - Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree of insulation degradation of one turn in the winding of a PMSWG. Cosimulation method by combining finite element model and external circuits is used. Hilbert–Huang transformation is applied to detect the very early stage fault in interturn insulation by analyzing the stator current. Detection results show that the minimum detectable severity degree of interturn fault in this paper is 0.1488%, which is much better than the best record in the literature.

AB - Incipient stator winding fault in permanent magnet synchronous wind generators (PMSWGs) is very difficult to be detected as the fault generated variations in terminal electrical parameters are very weak and chaotic. This paper simulates the incipient stator winding faults at different degree of insulation degradation of one turn in the winding of a PMSWG. Cosimulation method by combining finite element model and external circuits is used. Hilbert–Huang transformation is applied to detect the very early stage fault in interturn insulation by analyzing the stator current. Detection results show that the minimum detectable severity degree of interturn fault in this paper is 0.1488%, which is much better than the best record in the literature.

KW - Fault detection

KW - Hilbert–Huang transformation (HHT)

KW - Interturn insulation fault

KW - Permanent magnet synchronous wind generator (PMSWG)

U2 - 10.1109/TMAG.2014.2318207

DO - 10.1109/TMAG.2014.2318207

M3 - Journal article

VL - 50

JO - I E E E Transactions on Magnetics

JF - I E E E Transactions on Magnetics

SN - 0018-9464

IS - 11

M1 - 8206504

ER -