非线性动态网络/系统（N/S）模型辨识与故障诊断

采用方波脉冲函数变换（BPFT）对一类非线性动态N/S混合模型(H1,B)进行了辨识，导出了计算混合模型（H1,B）的相关公式和N/S响应的伏特劳级数解在方波域内的离散递推算式，解决了一类非线性动态N/S模型的数值计算问题.在此基础上，提出了一种基于多重预置模型的非线性N/S的故障诊断方法，该法通过检验各个预设模型与N/S当前状态的匹配程度来判断N/S是否处于某种故障状态，而无须在线估算N/S当前的模型及分析其特征，从而极大地减轻了在线计算工作量，可实现在线故障诊断.给出了故障诊断实例，实验结果表明该法故障诊断的准确率达到80％～90％.

Model Identification and Fault Diagnosis for Nonlinear Dynamic Networks /Systems (N/S)

By applying block-pulse function transform (BPFT) the hybrid model (H_1,B) for a class of nonlinear dynamic N/S was identified in the paper.The relative formulas for calculating the hybrid model (H_1,B) and discrete recursive formulas for computing Volterra series resolution of model of N/S were derived.Based on above a fault diagnosis method of multiple preset models for N/S was also proposed.This method can judge and classify the faults occurring in N/S by checking the matching degree between each preset model and the current working state of N/S.There is no need for computing the current model of N/S and analyzing the features on line.So the method can largely reduce the computational cost and the fault diagnosis can be realized on line.An example of fault diagnosis was given here.The results show that the accuracy of fault diagnosis reaches 80-90 percent by this means.