DocumentCode :
2623026
Title :
Fault feature extraction of ground-testing bed based on SNGA optimized KPCA
Author :
Feng, Zhigang ; Xu, Tao
Author_Institution :
Sch. of Autom., Shenyang Aerosp. Univ., Shenyang, China
fYear :
2011
fDate :
27-29 June 2011
Firstpage :
3244
Lastpage :
3247
Abstract :
To implement effective fault diagnosis of liquid propellant rocket engine ground-testing bed, the fault feature extraction method based on SNGA (Sharing function based niche genetic algorithm) optimized KPCA (Kernel principal component analysis) is studied. In the SNGA approach, the feature evaluation method is used to evaluate the classification ability of the feature extracted by KPCA, the comprehensive evaluation factor of all features is used as the fitness value. The hamming distance between every two individuals is defined as the sharing function. The method is experimented with the simulation data of the ground-testing bed. The comparison results of with and without optimization indicate that the feature extraction performance of KPCA is improved significantly with SNGA optimization. The comparison results of feature extraction by KPCA and PCA indicate that both feature extraction reliability and efficiency of KPCA are better than PCA in fault diagnosis of ground-testing bed.
Keywords :
condition monitoring; fault diagnosis; genetic algorithms; mechanical engineering computing; principal component analysis; propellants; rocket engines; KPCA; SNGA; comprehensive evaluation factor; fault diagnosis; fault feature extraction; ground-testing bed; hamming distance; kernel principal component analysis; liquid propellant rocket engine; optimization; sharing function based niche genetic algorithm; Engines; Fault diagnosis; Feature extraction; Genetic algorithms; Kernel; Principal component analysis; Rockets; KPCA(kernel principal component analysis); SNGA (sharing function based niche genetic algorithm); fault feature extraction; feature evaluation; ground-testing bed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
Type :
conf
DOI :
10.1109/CSSS.2011.5974816
Filename :
5974816
Link To Document :
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