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Application of rough set neural network in fault diagnosing of test-launching control system of missiles

机译:粗糙集神经网络在导弹试验控制系统故障诊断中的应用

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In test-launch control system of missiles, the relations between observed information and fault causes are complicated. Neural network is an effective method to diagnose this type of faults. But, to recede the complex of neural network is a main job in diagnosis. The rough sets theory was introduced in fault diagnosis via neural network to eliminate the unnecessary attributes and disclose the redundancy of condition attributes. Using the decision table, this approach extracted the diagnosis rules from the set of fault samples directly. A case study was used to illustrate the application of the proposed approach. Result shows that the approach is valid.
机译:在导弹的试验控制系统中,观察到的信息与故障原因之间的关系很复杂。神经网络是诊断这种类型的有效方法。但是,要使神经网络的复杂是诊断的主要工作。通过神经网络引入故障诊断中的粗糙集理论以消除不必要的属性并披露条件属性的冗余。使用决策表,此方法直接从该组故障样本中提取诊断规则。用于说明案例研究来说明所提出的方法的应用。结果表明该方法有效。

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