BF及模糊神经网络在旋转机械故障诊断中的应用

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本文对模糊神经网络用于故障诊断较传统BP(Back-Propagation)网络的优越性进行了分析,并提出了一种利用模糊神经网络进行旋转机械故障诊断的新方法.在这种方法中利用RBF(Radial Basis Function)神经网络获得隶属度函数,并简化了模糊神经网络的训练,使得新的故障诊断专家知识更易于扩充到现有的故障诊断网络中.仿真结果表明,本文方法所构建的故障诊断网络易于扩展且有良好的诊断效果.
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