Aiming at early stage latent faults of EHV large capacity transformers, a new fault diagnosis method based on mathematical morphology combined with multiple neural networks is presented.

针对超高压、大容量电力变压器的早期潜伏性故障，提出了一种基于数学形态学融合多神经网络的故障诊断新方法。

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Monitoring and analysis of the motor running status could detect fault in early phase and prevent the deterioration. Motor faults diagnosis is of great significance.

在电机运行时对其运行状态进行监测和分析可及早发现故障，防止故障的进一步恶化，具有十分重要的意义。

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