基于FARX和RBFNN模型的压铸机液压系统故障诊断

Fault Diagnosis Method Based on FARX and RBFNN Models

提出了一种基于FARX和RBFNN的压铸机液压系统故障诊断新方法。模糊化之后的ARX模型不仅保留了其自回归系数对故障状态变化规律反映非常敏感的特性,而且能够实现对非线性故障特征更准确的描述。故障诊断中首先对目标系统的故障状态建立FARX模型,提取其故障特征作为RBF网络训练样本,根据RBF网络的输出结果确定故障类型。仿真实例验证了此方法的准确性和有效性。

A new fault diagnosis method to hydraulic system for die casting machine based on FARX and RBFNN models was put forward.The ARX model after fuzzy processing not only retained its very sensitive response to fault state pattern,but also achieved more accurate description of non-linear features.Firstly,several FARX models were established for target system fault to extract their fault vectors.Secondly,the vectors were served as training source data and the RBF network classifier was established.Then,fault patterns could be identified according to the output of the classifier.A simulation verified the accuracy and availability of the method.