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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 Name: Journal of Engineering for Gas Turbines and Power; 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. doi:10.1115/1.4044683.
Mauricio, Alexandre, Sheng, Shuangwen, & Gryllias, Konstantinos. Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions. United States. doi: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. doi:10.1115/1.4044683.
@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 = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

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Works referenced in this record:

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