Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox

The wind turbine gearbox is a critical equipment transforming the speed of the rotor hub to the generator, the condition of which is the reflection of operational efficiency and reliability of wind turbines. As the initial stage of the wind turbine gearbox, the fault feature extraction of the planet...

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Main Authors: Jin XU, Xian DING, Zhu ZHANG, Lang CHEN
Format: Article
Language:English
Published: Institute of Fundamental Technological Research 2021-10-01
Series:Engineering Transactions
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Online Access:https://et.ippt.pan.pl/index.php/et/article/view/1326
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author Jin XU
Xian DING
Zhu ZHANG
Lang CHEN
author_facet Jin XU
Xian DING
Zhu ZHANG
Lang CHEN
author_sort Jin XU
collection DOAJ
description The wind turbine gearbox is a critical equipment transforming the speed of the rotor hub to the generator, the condition of which is the reflection of operational efficiency and reliability of wind turbines. As the initial stage of the wind turbine gearbox, the fault feature extraction of the planetary gear set is challenging since it is prone to be affected by complicated structure, vibration from other high-speed stages and background noise. In this paper, a double Q factor wavelet-based sparse decomposition is applied to the fault feature extraction of the wind turbine planetary gearbox. Considering the sparsest wavelet coefficients, the vibration signal is iteratively decomposed into high Q and low Q components. The fault feature is generally hidden in the low Q component. With further demodulation, the fault information of planetary gears can be easily detected.
format Article
id doaj-art-b10377885da24ebe8f15d7fa52d50636
institution Kabale University
issn 0867-888X
2450-8071
language English
publishDate 2021-10-01
publisher Institute of Fundamental Technological Research
record_format Article
series Engineering Transactions
spelling doaj-art-b10377885da24ebe8f15d7fa52d506362025-08-20T03:49:49ZengInstitute of Fundamental Technological ResearchEngineering Transactions0867-888X2450-80712021-10-0169410.24423/EngTrans.1326.20211004Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary GearboxJin XU0Xian DING1Zhu ZHANG2Lang CHEN3China Green Development Investment Group CO. LTD. Luneng Group CO. LTD.China Green Development Investment Group CO. LTD.Jiangsu Goldwind Science & Technology CO. LTD.Jiangsu Goldwind Science & Technology CO. LTD.The wind turbine gearbox is a critical equipment transforming the speed of the rotor hub to the generator, the condition of which is the reflection of operational efficiency and reliability of wind turbines. As the initial stage of the wind turbine gearbox, the fault feature extraction of the planetary gear set is challenging since it is prone to be affected by complicated structure, vibration from other high-speed stages and background noise. In this paper, a double Q factor wavelet-based sparse decomposition is applied to the fault feature extraction of the wind turbine planetary gearbox. Considering the sparsest wavelet coefficients, the vibration signal is iteratively decomposed into high Q and low Q components. The fault feature is generally hidden in the low Q component. With further demodulation, the fault information of planetary gears can be easily detected. https://et.ippt.pan.pl/index.php/et/article/view/1326wind turbine gearboxplanetary gearsdouble Q factor waveletsparse decomposition
spellingShingle Jin XU
Xian DING
Zhu ZHANG
Lang CHEN
Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
Engineering Transactions
wind turbine gearbox
planetary gears
double Q factor wavelet
sparse decomposition
title Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
title_full Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
title_fullStr Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
title_full_unstemmed Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
title_short Application of Double Q Wavelet-based Sparse Decomposition to Fault Feature Extraction of Wind Turbine Planetary Gearbox
title_sort application of double q wavelet based sparse decomposition to fault feature extraction of wind turbine planetary gearbox
topic wind turbine gearbox
planetary gears
double Q factor wavelet
sparse decomposition
url https://et.ippt.pan.pl/index.php/et/article/view/1326
work_keys_str_mv AT jinxu applicationofdoubleqwaveletbasedsparsedecompositiontofaultfeatureextractionofwindturbineplanetarygearbox
AT xianding applicationofdoubleqwaveletbasedsparsedecompositiontofaultfeatureextractionofwindturbineplanetarygearbox
AT zhuzhang applicationofdoubleqwaveletbasedsparsedecompositiontofaultfeatureextractionofwindturbineplanetarygearbox
AT langchen applicationofdoubleqwaveletbasedsparsedecompositiontofaultfeatureextractionofwindturbineplanetarygearbox