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TRANSFORMER FAILURE IDENTIFICATION AND LOCATION DIAGNOSIS METHOD BASED ON MULTI-STAGE TRANSFER LEARNING

机译:基于多阶段转移学习的变压器故障识别与位置诊断方法

摘要

A transformer failure identification and location diagnosis method based on a multi-stage transfer learning theory is provided. Simulation is set up first, a winding parameter of a transformer to be tested is calculated, and a winding equivalent circuit is accordingly built. Different failures are configured for the equivalent circuit, and simulation is performed to obtain a large number of sample data sets. A sweep frequency response test is performed on the transformer to be tested, and detection data sets are obtained. Initial network training is performed on simulation data sets by using the transfer learning method, and the detection data sets are further trained accordingly. A failure support matrix obtained through diagnosis is finally fused. The multi-stage transfer learning theory is provided by the disclosure.
机译:提供了基于多级传输学习理论的变压器故障识别与位置诊断方法。首先建立模拟,计算要进行测试的变压器的绕组参数,并因此构建绕组等效电路。不同的故障被配置为等效电路,并且执行模拟以获得大量的样本数据集。在要进行测试的变压器上执行扫描频率响应测试,并获得检测数据集。通过使用传输学习方法对仿真数据集执行初始网络训练,并且相应地训练检测数据集。通过诊断获得的失败支持矩阵最终融合。本公开提供了多级转移学习理论。

著录项

  • 公开/公告号US2021190882A1

    专利类型

  • 公开/公告日2021-06-24

    原文格式PDF

  • 申请/专利权人 WUHAN UNIVERSITY;

    申请/专利号US202017105616

  • 申请日2020-11-26

  • 分类号G01R31/62;G06N3/08;G06N3/04;

  • 国家 US

  • 入库时间 2022-08-24 19:31:45

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