Cross-domain Rotor Fault Diagnosis Method Based on Multi-scale Attention Domain Adaptation Network

XIANG Ling; HAN Zhongquan; BING Hankun; NI Wei; YE Feng

doi:10.19805/j.cnki.jcspe.2026.240805

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Cross-domain Rotor Fault Diagnosis Method Based on Multi-scale Attention Domain Adaptation Network

更新时间：2026-10-10

- Cross-domain Rotor Fault Diagnosis Method Based on Multi-scale Attention Domain Adaptation Network
- Chinese Journal of Power Engineering Vol. 46, Issue 4, Pages: 138-148(2026)
- 作者机构：
- 作者简介：
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- DOI：10.19805/j.cnki.jcspe.2026.240805
  CLC： TK268
- Published：2026
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向玲, 韩忠泉, 邴汉昆, 倪玮, 叶锋. 基于多尺度注意力域适应网络的跨域转子故障迁移诊断方法[J]. 动力工程学报, 2026, 46(4): 138-148.
向玲, 韩忠泉, 邴汉昆, 倪玮, 叶锋. 基于多尺度注意力域适应网络的跨域转子故障迁移诊断方法[J]. 动力工程学报, 2026, 46(4): 138-148. DOI： 10.19805/j.cnki.jcspe.2026.240805.

DOI： 10.19805/j.cnki.jcspe.2026.240805

摘要

针对源域和目标域数据分布差异大及现场故障标签样本难获取而导致诊断精度低的问题

提出了基于多尺度注意力域适应网络(MADAN)的跨域转子故障迁移诊断方法。使用多尺度卷积层直接提取振动信号的深层故障特征;利用空间和通道注意力捕捉重要特征的所属空间位置和通道

并增大其过程传递的权重

进一步增强特征的表达能力;依据域适应方法优化源域与目标域提取特征分布的差异问题

以提高迁移诊断性能。结果表明:相比于其他诊断方法

MADAN方法在跨实验台转子故障迁移任务中具有更高的诊断精度

为跨设备转子故障迁移诊断提供了新的参考。

Abstract

To address the issue of significant differences in data distribution between source domain and target domain

as well as the difficulty in obtaining on-site fault label samples

which lead to low diagnostic accuracy

a cross-domain rotor fault transfer diagnosis method based on multi-scale attention domain adaptation network (MADAN) was proposed. Multiscale convolutional layers were used to directly extract deep fault features of vibration signals. Spatial and channel attention were employed to capture the spatial positions and channels where important features located

and to increase the weights of process transmission

thereby further enhancing the expression ability of the features. Based on the domain adaptation method

the differences in the feature distribution extracted from the source domain and the target domain were optimized to improve the performance of transfer diagnosis. Results show that compared to other diagnostic methods

the MADAN approach achieves higher diagnostic accuracy in cross-rig rotor fault transfer tasks

providing new reference value for cross-device rotor fault transfer diagnosis.

关键词

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references

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Related Institution

Hebei Key Laboratory of Electric Machinery Health Maintenance & Failure Prevention, North China Electric Power University

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