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Vibration trend prediction of pumped storage units based on VMD and GRU

机译:基于VMD和GRU的泵送存储单元的振动趋势预测

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摘要

Effective prediction of vibration signals can provide an important basis for early warning of performance degradation and failure of pumped storage units. This paper proposes a vibration signal prediction method for pumped storage units based on variational mode decomposition (VMD) and gated recurrent unit neural network (GRU). The VMD-GRU prediction method has a significant improvement in effectiveness and prediction accuracy, which is of great application significance in actual engineering.
机译:有效预测振动信号可以为泵浦存储单元的性能下降和故障的预警提供重要依据。 本文提出了一种基于变分模分解(VMD)和门控复发单元神经网络(GRU)的泵浦存储单元的振动信号预测方法。 VMD-GRU预测方法具有显着提高的有效性和预测精度,这在实际工程中具有很大的应用意义。

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