线性主成分分析是一种线性分析方法，而数据通常是非线性的。
Principal component analysis is a linear method, but the most data are nonlinear.
针对减速箱运行状态和特征参数之间存在的复杂非线性关系，提出了基于主成分分析的RBF神经网络减速箱运行状态诊断方法。
As to the complicated nonlinear relation existing between running status of gear reducer and characteristic parameters, PCA-based RBF neural network reducer running status diagnostics is put forward.
论文中重点介绍了该种方法的降维思想，以及用主成分分析方法、对应分析方法和非线性映射方法解决问题的步骤。
In this paper, the emphasis is placed on the technique for reducing the dimensions. The principal analysis, correspondence analysis and nonlinear mapping are described in detail.
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