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针对液压系统的故障诊断,提出融合系统状态信息作为系统特征向量,引入RBF神经网络作为模式识别分类算法的智能诊断方法。并论述采用RBF神经网络作为分类算法的可行性及其优势。最后以电液位置伺服系统为例,建立相关的RBF网络,验证以上的陈述。
Aiming at the fault diagnosis of hydraulic system, this paper proposes the intelligent diagnosis method of integrating the state information of the system as the system eigenvector and introducing the RBF neural network as the pattern recognition classification algorithm. And discusses the feasibility and advantage of using RBF neural network as classification algorithm. Finally, taking the electro-hydraulic position servo system as an example, establish the relevant RBF network and verify the above statements.