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基于TAMamba-BiGRU的晶闸管变流器换相失败诊断方法

薛振宇 郭来功 张俊飞 马龙

湖北民族大学学报(自然科学版)2026,Vol.44Issue(2):161-165,191,6.
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湖北民族大学学报(自然科学版)2026,Vol.44Issue(2):161-165,191,6.DOI:10.13501/j.cnki.42-1908/n.2026.06.001

基于TAMamba-BiGRU的晶闸管变流器换相失败诊断方法

Thyristor Converter Commutation Failure Diagnosis Method Based on TAMamba-BiGRU

薛振宇 1郭来功 1张俊飞 1马龙2

作者信息

  • 1. 安徽理工大学 电气与信息工程学院,安徽 淮南 232001
  • 2. 中煤科工集团沈阳研究院有限公司,辽宁 抚顺 113122
  • 折叠

摘要

Abstract

To address the problem that commutation failure features of thyristor converters were easily submerged under strong noise interference,leading to degraded diagnostic accuracy,a thyristor converter commutation failure diagnosis model integrating time aware Mamba and bidirectional gated recurrent unit(TAMamba-BiGRU)was proposed.Firstly,one-dimensional data was transformed into two-dimensional feature image using the Gramian angular difference field(GADF).Subsequently,a dual-branch architecture was constructed:the data in the one-dimensional branch were linearly projected to a higher-dimensional space to form high-dimensional sequences,while image features were extracted by a residual network(ResNet)in the two-dimensional branch and further transformed into sequence representations.The two sequences were fused through cross attention and fed into TAMamba module to capture long-range sequence dependencies and rapid dynamic variations,followed by further bidirectional temporal refinement using the BiGRU.Finally,the output features were fed into a fully connected layer to achieve commutation failure fault classification.The results demonstrated that a diagnostic accuracy of 91.52%was still achieved by the TAMamba-BiGRU model under a strong noise condition with a signal-to-noise ratio of 2dB.The model was shown to be effective for commutation failure diagnosis in thyristor converters.

关键词

换相失败/晶闸管变流器/时间感知/交叉注意力/双向门控循环单元

Key words

commutation failure/thyristor converter/time aware/cross attention/bidirectional gated recurrent unit

分类

信息技术与安全科学

引用本文复制引用

薛振宇,郭来功,张俊飞,马龙..基于TAMamba-BiGRU的晶闸管变流器换相失败诊断方法[J].湖北民族大学学报(自然科学版),2026,44(2):161-165,191,6.

基金项目

国家自然科学基金项目(52474191). (52474191)

湖北民族大学学报(自然科学版)

2096-7594

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