A fault detection algorithm based on wavelet denoising and KPCA

Advances in Intelligent and Soft Computing

Volumn 159 AISC, Issue VOL. 1, 2012, Pages 311-317

  Zhao, Xiaoqiang ^a   Wang, Xinming ^b  

^a LANZHOU UNIVERSITY OF TECHNOLOGY   (China)

^b Gansu Province Medical Science Institute   (China)

Author keywords

Fault detection; KPCA; TE processes; Wavelet denoising

Indexed keywords

DE-NOISE; DETECTION METHODS; FAULT DETECTION ALGORITHM; FEATURE SPACE; INPUT SPACE; KERNEL PRINCIPAL COMPONENT ANALYSES (KPCA); KPCA; LINEAR PROBLEMS; NONLINEAR PROBLEMS; PCA METHOD; POOR PERFORMANCE; RANDOM DISTURBANCES; TE PROCESS; TENNESSEE EASTMAN; WAVELET DENOISING;

CHEMICAL INDUSTRY; CONTROL SYSTEMS; FAULT DETECTION; PRINCIPAL COMPONENT ANALYSIS;

WAVELET TRANSFORMS;

EID: 84861044205     PISSN: 18675662     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-29387-0_46     Document Type: Conference Paper

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