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Title: Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

Abstract

Digitally enhanced services for wind power could reduce Operations and Maintenance costs as well as the Levelised Cost Of Energy. Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things and Big Data Analytics. The heart of wind turbines is an epicyclic gearbox and rolling element bearings are often responsible for machinery stops. The vibration signatures of bearings are rather weak compared to other components. As a result a number of signal processing techniques have been proposed, focusing towards accurate and early fault detection with limited false alarms and missed detections. In Envelope Analysis an envelope of the vibration signal is estimated usually after filtering around a frequency band. Different tools, such as Kurtogram, have been proposed to select the optimum filter parameters. Monitoring techniques have reached a mature level for steady speed and load operating conditions. On the other hand, under chaniging operating conditions, it is still unclear whether the change of the monitoring indicators is due to the change of the machinery's health or due to the change of operating parameters. Recently, the authors have proposed a new tool called IESFOgram, based on Cyclic Spectral Coherence for the automaticmore » selection of the filtering band. In this paper, the performance of the tool is evaluated on the National Renewable Energy Laboratory wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.« less

Authors:
 [1]; ORCiD logo [2];  [1]
  1. Katholieke Univ. Leuven, Heverlee (Belgium)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1567032
Report Number(s):
NREL/JA-5000-74369
Journal ID: ISSN 0742-4795
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Engineering for Gas Turbines and Power
Additional Journal Information:
Journal Volume: 142; Journal Issue: 3; Journal ID: ISSN 0742-4795
Publisher:
ASME
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind energy; wind turbine; gearbox; condition monitoring; cyclostationary analysis; cyclic spectral coherence

Citation Formats

Mauricio, Alexandre, Sheng, Shuangwen, and Gryllias, Konstantinos. Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions. United States: N. p., 2019. Web. https://doi.org/10.1115/1.4044683.
Mauricio, Alexandre, Sheng, Shuangwen, & Gryllias, Konstantinos. Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions. United States. https://doi.org/10.1115/1.4044683
Mauricio, Alexandre, Sheng, Shuangwen, and Gryllias, Konstantinos. Thu . "Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions". United States. https://doi.org/10.1115/1.4044683. https://www.osti.gov/servlets/purl/1567032.
@article{osti_1567032,
title = {Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions},
author = {Mauricio, Alexandre and Sheng, Shuangwen and Gryllias, Konstantinos},
abstractNote = {Digitally enhanced services for wind power could reduce Operations and Maintenance costs as well as the Levelised Cost Of Energy. Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things and Big Data Analytics. The heart of wind turbines is an epicyclic gearbox and rolling element bearings are often responsible for machinery stops. The vibration signatures of bearings are rather weak compared to other components. As a result a number of signal processing techniques have been proposed, focusing towards accurate and early fault detection with limited false alarms and missed detections. In Envelope Analysis an envelope of the vibration signal is estimated usually after filtering around a frequency band. Different tools, such as Kurtogram, have been proposed to select the optimum filter parameters. Monitoring techniques have reached a mature level for steady speed and load operating conditions. On the other hand, under chaniging operating conditions, it is still unclear whether the change of the monitoring indicators is due to the change of the machinery's health or due to the change of operating parameters. Recently, the authors have proposed a new tool called IESFOgram, based on Cyclic Spectral Coherence for the automatic selection of the filtering band. In this paper, the performance of the tool is evaluated on the National Renewable Energy Laboratory wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.},
doi = {10.1115/1.4044683},
journal = {Journal of Engineering for Gas Turbines and Power},
number = 3,
volume = 142,
place = {United States},
year = {2019},
month = {8}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

TABLE 1 TABLE 1: Power and speed details of the 4 measurement cases.

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Works referenced in this record:

Fast computation of the spectral correlation
journal, August 2017


A peak Energy Criterion (p. e.) for the Selection of Resonance Bands in Complex Shifted Morlet Wavelet (Csmw) Based Demodulation of Defective Rolling Element Bearings Vibration Response
journal, July 2009

  • Gryllias, Konstantinos C.; Antoniadis, Ioannis
  • International Journal of Wavelets, Multiresolution and Information Processing, Vol. 07, Issue 04
  • DOI: 10.1142/S0219691309002982

Robust wind turbine gearbox fault detection: Robust wind turbine gearbox fault detection
journal, January 2013

  • Sheldon, Jeremy; Mott, Genna; Lee, Hyungdae
  • Wind Energy, Vol. 17, Issue 5
  • DOI: 10.1002/we.1567

Vibration monitoring of rolling element bearings by the high-frequency resonance technique — a review
journal, February 1984


The spectral analysis of cyclo-non-stationary signals
journal, June 2016


Cyclic spectral analysis in practice
journal, February 2007


Rolling element bearing diagnostics—A tutorial
journal, February 2011


Optimised Spectral Kurtosis for bearing diagnostics under electromagnetic interference
journal, June 2016


    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.