To deal with the problem of Debris' feature extraction with the characteristic of large scale number in description parameter and nonlinear relationship among these parameters, a KPCA-based method is presented. Based on the detailed introduction of KPCA algorithm, a real case was studied for the purpose of constructing a debris automatic recognition sub-system which can be served for diesel engine fault detection and analysis system. The results of experimental research and a comparison with linear PCA demonstrate that KPCA-based approach is feasible and valid for synthesizing nonlinear characteristic parameter and reducing feature dimension.
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李岳,温熙森,吕克洪.基于核主成分分析的铁谱磨粒特征提取方法研究[J].国防科技大学学报,2007,29(2):113-116. LI Yue, WEN Xisen, Lü Kehong. KPCA-based Technique for Debris Feature Extraction[J]. Journal of National University of Defense Technology,2007,29(2):113-116.