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.
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。
The results of PCA and DPC show that the sampling data have a remarkable nonlinear structure.
PCA和DPC分析结果表明，取样数据具有明显的非线性结构。
An improved PCA arithmetic model is applicable to nonlinear plant thermal processes using local PCA model for various power loads based on the historical data.
为了使基于PCA的传感器故障检测和重构方法适用于非线性较严重的热工过程，对该方法进行了有效的改进。
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