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Hydro-generator units operating condition forecasting and fault diagnosis based on GANN

机译:基于GANN的水轮发电机组运行状态预测与故障诊断

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In this paper, from the Angle to predict, take hydro-generating operation condition parameters (head, power) as input sample, take unit head cover vibration as output sample, create BP and GANN neural network prediction model. Train the established models, through comparing the two models. GANN model Has better precision.
机译:本文从角度进行预测,以水力发电工况参数(扬程,功率)为输入样本,以机组顶盖振动为输出样本,建立BP和GANN神经网络预测模型。通过比较两个模型来训练已建立的模型。 GANN模型具有更好的精度。

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