Residual signal feature extraction for gearbox planetary stage fault detection

Georgios Alexandros Skrimpas, Thomas Ursin, Christian Walsted Sweeney, Kun Saptohartyadi Marhadi, Nenad Mijatovic, Joachim Holbøll

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work, statistical features measuring the signal energy and Gaussianity are calculated from the residual signals between each pair from the first to the fifth tooth mesh frequency of the meshing process in a multi-stage wind turbine gearbox. The suggested algorithm includes resampling from time to angular domain, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed approach and the possibility of characterizing a fault as localized or distributed.
Original languageEnglish
JournalWind Energy
Volume20
Issue number8
Pages (from-to)1389-1404
Number of pages16
ISSN1095-4244
DOIs
Publication statusPublished - 2017

Keywords

  • Wind turbine
  • Planetary stage
  • Vibration analysis
  • Differential entropy

Cite this

Skrimpas, Georgios Alexandros ; Ursin, Thomas ; Sweeney, Christian Walsted ; Marhadi, Kun Saptohartyadi ; Mijatovic, Nenad ; Holbøll, Joachim. / Residual signal feature extraction for gearbox planetary stage fault detection. In: Wind Energy. 2017 ; Vol. 20, No. 8. pp. 1389-1404.
@article{1cfbe16824da4df8b489bc45d19f68be,
title = "Residual signal feature extraction for gearbox planetary stage fault detection",
abstract = "Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work, statistical features measuring the signal energy and Gaussianity are calculated from the residual signals between each pair from the first to the fifth tooth mesh frequency of the meshing process in a multi-stage wind turbine gearbox. The suggested algorithm includes resampling from time to angular domain, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed approach and the possibility of characterizing a fault as localized or distributed.",
keywords = "Wind turbine, Planetary stage, Vibration analysis, Differential entropy",
author = "Skrimpas, {Georgios Alexandros} and Thomas Ursin and Sweeney, {Christian Walsted} and Marhadi, {Kun Saptohartyadi} and Nenad Mijatovic and Joachim Holb{\o}ll",
year = "2017",
doi = "10.1002/we.2099",
language = "English",
volume = "20",
pages = "1389--1404",
journal = "Wind Energy",
issn = "1095-4244",
publisher = "JohnWiley & Sons Ltd.",
number = "8",

}

Residual signal feature extraction for gearbox planetary stage fault detection. / Skrimpas, Georgios Alexandros; Ursin, Thomas; Sweeney, Christian Walsted; Marhadi, Kun Saptohartyadi; Mijatovic, Nenad; Holbøll, Joachim.

In: Wind Energy, Vol. 20, No. 8, 2017, p. 1389-1404.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Residual signal feature extraction for gearbox planetary stage fault detection

AU - Skrimpas, Georgios Alexandros

AU - Ursin, Thomas

AU - Sweeney, Christian Walsted

AU - Marhadi, Kun Saptohartyadi

AU - Mijatovic, Nenad

AU - Holbøll, Joachim

PY - 2017

Y1 - 2017

N2 - Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work, statistical features measuring the signal energy and Gaussianity are calculated from the residual signals between each pair from the first to the fifth tooth mesh frequency of the meshing process in a multi-stage wind turbine gearbox. The suggested algorithm includes resampling from time to angular domain, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed approach and the possibility of characterizing a fault as localized or distributed.

AB - Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work, statistical features measuring the signal energy and Gaussianity are calculated from the residual signals between each pair from the first to the fifth tooth mesh frequency of the meshing process in a multi-stage wind turbine gearbox. The suggested algorithm includes resampling from time to angular domain, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed approach and the possibility of characterizing a fault as localized or distributed.

KW - Wind turbine

KW - Planetary stage

KW - Vibration analysis

KW - Differential entropy

U2 - 10.1002/we.2099

DO - 10.1002/we.2099

M3 - Journal article

VL - 20

SP - 1389

EP - 1404

JO - Wind Energy

JF - Wind Energy

SN - 1095-4244

IS - 8

ER -