红水河2024，Vol.43Issue(1)：102-105,111,5.DOI:10.3969/j.issn.1001-408X.2024.01.019
基于数据增强技术的LSTM模型变压器故障诊断研究
Transformer Fault Diagnosis of LSTM Model Based on Data Enhancement Technology
蔡晨1
作者信息
- 1. 柳州铁道职业技术学院 继续教育学院, 广西 柳州 545616
- 折叠
摘要
Abstract
In order to solve the problems of relying on manual experience in transformer fault diagnosis and improve the ability of transformer fault diagnosis,the author proposes a transformer fault diagnosis method based on data enhanced long short-term memory(LSTM)model.Firstly,the data sample size is increased by data enhancement technology,then the transformer fault diagnosis model is constructed by LSTM,and finally the transformer fault diagnosis experiment is carried out.The results show that the accuracy rate,precision rate,recall rate and F1 value of this method are 0.998;Compared with the support vector machine model,each evaluation index is increased by at least 8%.This method can improve the ability of transformer fault diagnosis and contribute to the diagnosis and maintenance of transformer faults.关键词
变压器/故障诊断/数据增强/LSTM模型Key words
transformer/fault diagnosis/data enhancement/LSTM model分类
动力与电气工程引用本文复制引用
蔡晨..基于数据增强技术的LSTM模型变压器故障诊断研究[J].红水河,2024,43(1):102-105,111,5.
