Application of Machine Learning in Transformer Fault Diagnosis

MA Hongbin; YANG Fei; YANG Leina; ZHANG Ran

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Application of Machine Learning in Transformer Fault Diagnosis

更新时间：2025-04-27

- Application of Machine Learning in Transformer Fault Diagnosis
- Vol. 40, Issue 4, Pages: 35-38(2021)
- 作者机构：
  
  国网山东省电力公司枣庄供电公司
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM407;TP181
- Published：2021
- 稿件说明：
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MA Hongbin, YANG Fei, YANG Leina, et al. Application of Machine Learning in Transformer Fault Diagnosis[J]. 2021, 40(4): 35-38.
DOI：

MA Hongbin, YANG Fei, YANG Leina, et al. Application of Machine Learning in Transformer Fault Diagnosis[J]. 2021, 40(4): 35-38. DOI：

摘要

当前变压器故障诊断主要采用油中气体分析法(IEC三比值法)

在实际应用中诊断的准确率偏低

只有80%左右。通过将机器学习与变压器故障诊断相结合

搭建了故障诊断模型

同时采用集成学习

综合多个基分类器

将故障识别的准确率提高到了92.5%。

Abstract

At present

gas in oil analysis method（IEC three ratio method） is mainly used for transformer fault diagnosis.In practical application

the accuracy of diagnosis is low

only about 80%.By combining machine learning with transformer fault diagnosis

a fault diagnosis model is built.At the same time

integrated learning and multiple base classifiers are used to improve the accuracy of fault recognition to 92.5%.

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