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The research of Neural Network and EMD Methods used in the Prediction of Machine Running State

机译:用于预测机器运行状态的神经网络和EMD方法研究

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The paper puts forward a method of ventilator running state prediction which is based on EMD and Neural Network, which aims at ventilator's non-stationary vibration signals. First of all, vibration data are decomposed into eight intrinsic mode signals and one residual quantity by EMD. Then Neural Network is adopted to predict the decomposition components and reconstruct them. Finally, the final prediction results are achieved. In this paper, the ventilator vibration signals of Tangshan Iron and Steel Group Coking Plant from March 1, 2012 to July 1, 2012 are used as the research data. Comparative study method is adopted to compare this prediction method with direct Neural Network prediction in terms of results, which shows that this method has better accuracy.
机译:本文提出了一种基于EMD和神经网络的呼吸机运行状态预测方法,其目的是呼吸机的非静止振动信号。首先,振动数据通过EMD分解为八个内在模式信号和一个残余量。然后采用神经网络来预测分解组件并重建它们。最后,实现了最终预测结果。本文将于2012年3月1日至2012年7月1日唐山钢铁集团焦化厂的呼吸机振动信号用作研究数据。采用比较研究方法将这种预测方法与直接神经网络预测进行比较,结果表明该方法具有更好的准确性。

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