主成分分析法, 核主成分分析法, 核函数, 神经网络, 支持向量机, 机械噪声, 降维

According to the classification principle of linear and non-linear dimensional reduction,this paper dealt with mechanical noise data under different working-modes through PCA and KPCA. Lastly,the paper computed the right recognition percentage of noise data, including had been reduced and not, by NN method and SVM method, and compared the excellence for PCA and KPCA in dimensional reduction. Consequently, a better method of dimensional reduction is selected for ribbed cylindrical double-shells according to the results.

PCA(principal components analysis), KPCA(kernel PCA), kernel function, NN(neural network), SVM(support vector machine), mechanical noise, dimensional reduction