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TRANSFORMER FAILURE DIAGNOSIS METHOD AND SYSTEM BASED ON INTEGRATED DEEP BELIEF NETWORK

机译:基于集成深度信仰网络的变压器故障诊断方法和系统

摘要

A transformer failure diagnosis method and system based on an integrated deep belief network are provided. The disclosure relates to the fields of electronic circuit engineering and computer vision. The method includes the following: obtaining a plurality of vibration signals of transformers of various types exhibiting different failure types, retrieving a feature of each of the vibration signals, and establishing training data through the retrieved features; training a plurality of deep belief networks exhibiting different learning rates through the training data and obtaining a failure diagnosis correct rate of each of the deep belief networks; and keeping target deep belief networks corresponding to the failure diagnosis correct rates that satisfy requirements, building an integrated deep belief network through each of the target deep belief networks, and performing a failure diagnosis on the transformers through the integrated deep belief network.
机译:提供了一种基于集成深度信念网络的变压器故障诊断方法和系统。本公开涉及电子电路工程和计算机视觉领域。该方法包括以下内容:获得具有不同故障类型的各种类型的变压器的多个振动信号,检索每个振动信号的特征,并通过检索的特征建立训练数据;通过训练数据训练多个深度信仰网络,并通过训练数据获得不同的学习率,并获得每个深度信仰网络的失败诊断正确率;并保持目标深度信念网络对应的失败诊断正确的速率,满足要求,通过每个目标深度信仰网络构建集成的深度信仰网络,并通过集成的深度信仰网络对变压器进行故障诊断。

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