Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine

Renewable Energy

Volumn 62, Issue , 2014, Pages 1-9

  Tang, Baoping ^a   Song, Tao ^a   Li, Feng ^b   Deng, Lei ^a  

^a CHONGQING UNIVERSITY   (China)

^b SICHUAN UNIVERSITY   (China)

Author keywords

Fault diagnosis; Manifold learning; Orthogonal neighborhood preserving embedding (ONPE); Shannon wavelet support vector machine; Wind turbine transmission system

Indexed keywords

FAULT DIAGNOSIS APPLICATIONS; MANIFOLD LEARNING; MANIFOLD LEARNING ALGORITHM; NON-STATIONARY VIBRATION SIGNALS; NONLINEAR DIMENSIONALITY REDUCTION; ORTHOGONAL NEIGHBORHOOD PRESERVING EMBEDDING; SHANNON WAVELET; TRANSMISSION SYSTEMS;

EIGENVALUES AND EIGENFUNCTIONS; FAILURE ANALYSIS; SUPPORT VECTOR MACHINES; TRANSMISSIONS; WAVELET TRANSFORMS;

WIND TURBINES;

ACCURACY ASSESSMENT; ALGORITHM; COST-BENEFIT ANALYSIS; EIGENVALUE; MAINTENANCE; NONLINEARITY; VIBRATION; WAVELET ANALYSIS; WIND TURBINE;

EID: 84880675844     PISSN: 09601481     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.renene.2013.06.025     Document Type: Article

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