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Diagnosis of non-linear mixed multiple faults based on underdetermined blind source separation for wind turbine gearbox: simulation, testbed and realistic scenarios

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Diagnosis of non-linear mixed multiple faults based on underdetermined blind source separation for wind turbine gearbox: simulation, testbed and realistic scenarios

Content Provider	IET Digital Library
Author	Hu, Chun zhi Yang, Qiang Huang, Miao ying Yan, Wen jun
Abstract	The diagnosis of multi-fault in wind turbine gearbox based on vibration signal processing is considered challenging as the collected measurements from acceleration transducers are often a non-linear mixture of signals induced from an unknown number of sources, i.e. an underdetermined blind source separation (UBSS) problem. In this study, a novel UBSS-based algorithmic solution is proposed to address this technical challenge from two aspects: source number estimation and source signal recovery. The former is realised based on the empirical mode decomposition and singular value decomposition (SVD) joint approach; and for the latter, the observed vibration signals are transformed to the time-frequency domain using short-time Fourier transform to obtain the sparse representation of the signals. The fuzzy C-means clustering and l 1 norm decomposition are carried out to estimate the mixing matrix and recover the source signals, respectively. The performance of proposed solution is extensively assessed through experiments based on simulation, testbed and realistic wind farm measurements for a range of fault scenarios for both linear and non-linear scenarios. The numerical result clearly confirms the effectiveness of the proposed algorithmic solution for non-linear multi-fault diagnosis of wind turbines.
Starting Page	1418
Ending Page	1429
Page Count	12
ISSN	17521416
Volume Number	11
e-ISSN	17521424
Issue Number	Issue 11, Sep (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/11/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2016.0982
Journal	IET Renewable Power Generation
Publisher Date	2017-06-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acceleration Transducer Algebra Blind Source Separation Combinatorial Mathematics Empirical Mode Decomposition Fault Diagnosis Fourier Transforms Fuzzy C-means Clustering Fuzzy Set Theory Gears Integral Transforms L1 Norm Decomposition Matrix Algebra Mixing Matrix Estimation Nonlinear Mixed Multiple Fault Diagnosis Nonlinear Signal Mixture Power Generation Fault Power System Measurement Power System Measurement And Metering Short-time Fourier Transform Signal Processing And Detection Signal Representation Singular Value Decomposition Source Number Estimation Source Signal Recovery Sparse Signal Representation SVD Time-frequency Analysis Time-frequency Domain Analysis UBSS Problem Underdetermined Blind Source Separation Vibration Signal Processing Vibration Signal Transformation Wind Farm Measurement Wind Power Plant Wind Turbine Wind Turbine Gearbox
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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