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。
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。
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。
应用推荐