Wavelet kernel entropy component analysis with application to industrial process monitoring

Neurocomputing

Volumn 147, Issue 1, 2015, Pages 395-402

  Yang, Yinghua ^a   Li, Xiaole ^a   Liu, Xiaozhi ^a   Chen, Xiaobo ^a  

^a NORTHEASTERN UNIVERSITY   (China)

Author keywords

Fault identification; Kernel entropy component analysis; Process monitoring; TE process; Wavelet transform

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; FAULT DETECTION; FEATURE EXTRACTION; PROCESS CONTROL; PROCESS MONITORING;

CHARACTERISTICS OF COMPLEXITY; COMPONENT ANALYSIS; EIGENVALUES AND EIGENVECTORS; FAULT IDENTIFICATIONS; FEATURE EXTRACTION METHODS; INDUSTRIAL PROCESS MONITORING; PRINCIPAL COMPONENTS; TE PROCESS;

WAVELET TRANSFORMS;

ARTICLE; CONTROLLED STUDY; FAULT DETECTION; INFORMATION PROCESSING; KERNEL ENTROPY COMPONENT ANALYSIS; KERNEL METHOD; KERNEL PRINCIPAL COMPONENT ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROCESS MONITORING; PROCESS TECHNOLOGY; SIMULATION; TENNESSEE EASTMAN PROCESS; WAVELET ANALYSIS;

EID: 84924086238     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.06.045     Document Type: Article

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