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Study of predicting breakdown voltage of stator insulation in generator based on BP neural network

机译:基于BP神经网络的发电机定子绝缘击穿电压预测研究。

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The breakdown voltage plays an important role in evaluating residual life of stator insulation in generator. In this paper, we discussed BP neural network that was used to predict the breakdown voltage of stator insulation in generator of 300 MW/18 kV. At first the neural network has been trained by the samples that include the varieties of dielectric loss factor tanδ , the partial discharge parameters and breakdown voltage. Then we tried to predict the breakdown voltage of samples and stator insulations subjected to multi-stress aging by the trained neural network. We found that it's feasible and accurate to predict the voltage. This method can be applied to predict breakdown voltage of other generators which have the same insulation structure and material.
机译:击穿电压在评估发电机定子绝缘的剩余寿命中起着重要作用。在本文中,我们讨论了用于预测300 MW / 18 kV发电机定子绝缘故障电压的BP神经网络。最初,神经网络已经通过样本训练,样本包括各种介电损耗因子tanδ,局部放电参数和击穿电压。然后,我们尝试通过训练后的神经网络预测经受多应力老化的样品和定子绝缘的击穿电压。我们发现预测电压是可行且准确的。该方法可用于预测具有相同绝缘结构和材料的其他发电机的击穿电压。

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