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Research of Fault Diagnosis System for Pickling and Cold-rolling Electric Drives Based on BP Neural Network

机译:基于BP神经网络的酸洗和冷轧电动驱动器故障诊断系统研究

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The Paper has exploited a system of on-line monitoring and fault diagnosis for pickling and cold-rolling electric drives, making use of configuration technologies, Matlab simulation tools and BP neural network. Based on the theory of BP neural network, a fault diagnosis model is designed, which is for electro-hydraulic servo valve, the key execute machine of pickling and cold-rolling electric drives. The model is directed at analyzing the fault possibility and fault type of electro-hydraulic servo valve. After tests on the well-trained BP-based fault diagnosis system, the system proves to have the ability of diagnosing any type of fault of electro-hydraulic servo valve accurately. The result of experiment gives the evidence that this method is very efficient for fault diagnosis system for pickling and cold-rolling electric drives.
机译:本文利用了一种用于酸洗和冷轧电动驱动器的在线监测和故障诊断系统,利用配置技术,MATLAB仿真工具和BP神经网络。基于BP神经网络理论,设计了故障诊断模型,适用于电动液压伺服阀,酸洗和冷轧电动驱动器的关键执行机。该模型旨在分析电液伺服阀的故障可能性和故障类型。在测试良好的基于​​BP的故障诊断系统之后,系统证明能够精确诊断任何类型的电动液伺服阀故障的能力。实验结果提供了证据表明这种方法对于酸洗和冷轧电动驱动器的故障诊断系统非常有效。

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