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Gear fault diagnosis method of intelligence based on genetic algorithm to optimize the BP neural network

机译:基于遗传算法优化BP神经网络的智能齿轮故障诊断方法

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The work of the gear transmission is very complex, and its failure in the form and features tend to show non-linear mapping. Fault signal is often submerged in conventional vibration signal and noise, it is not easy using traditional signal processing methods to extract fault features which in a difficult to gear fault diagnosis. This paper based on the genetic algorithm to optimize the structure of the BP neural network model for the intelligent diagnosis system which is used in gear fault diagnosis. The experimental results show that this method can be effectively used for the diagnosis and identification of the gears common fault type.
机译:齿轮传动的工作非常复杂,并且其形式和特征的故障倾向于显示非线性映射。故障信号经常在传统的振动信号和噪声中浸没,使用传统信号处理方法并不容易提取故障特征,这在难以进行齿轮故障诊断。本文基于遗传算法优化齿轮故障诊断智能诊断系统BP神经网络模型的结构。实验结果表明,该方法可以有效地用于齿轮常见故障类型的诊断和识别。

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