基于神经网络的多模态故障检测

研究了使用RBF网络进行多模态辨识的结构和其在多模态故障检测中的应用。在信号满足持续激励的条件下 ,状态估计误差渐进趋向于零 ,辨识器的参数估计能够达到满意的效果。使用多个神经网络辨识器 ,对一非线性系统的多模态故障检测进行了仿真研究

Neural Networks-Based Multiple Mode Failure Detection

Multiple mode identification structure using radial basis function (RBF) neural network and its application to the multimodefailure detection is studied in this paper. The state estimation error convergesto zero and parameters of the identifier converge to the ideal parameters provided that persistency of excitation condition is fulfilled.A simulation is presented for multi-model failure detection for a nonlinear system using multiple neural network identifiers.