【目的】匝间短路故障是电路系统及电机驱动系统中常见且隐蔽的早期故障类型,不同相故障在物理机理上具有一致性,但受相位差异与测量条件影响,其数据分布存在显著差异,给数据驱动诊断方法的跨相应用带来挑战。本文提出一种在有限标注条件下实现不同相匝间短路故障的统一诊断方法。【方法】将相别差异视为一种特定形式的数据分布偏移,因此匝间短路的核心判据与具体相位无关。基于此,本文从跨相迁移的角度出发,提出一种仅利用单一相匝间短路故障数据进行模型训练,并将其直接应用于其他相故障诊断的可行性方法。该方法通过构建具有物理一致性的特征表示,并采用统一的轻量化诊断模型,以此实现单相训练条件下的多相匝间短路故障识别。【结果】结果表明,在不引入复杂迁移结构和额外标注数据的前提下,所提出的方法在训练相上具有较高诊断精度,并能够在不同相匝间短路故障诊断任务中保持稳定性能,显著提升了故障诊断的跨相泛化能力。【结论】该研究为降低匝间短路故障诊断模型对多相标注数据的依赖、提升模型在实际工程场景中的可推广性提供了一种简洁而有效的解决思路,具有较高的工程实用价值。

[Objective] Inter-turn short-circuit faults are a common and latent early-stage failures in circuit and motor drive systems. Although the underlying physical mechanisms of such faults are essentially identical across different phases, significant discrepancies in data distributions arise due to phase shifts and measurement conditions, which limits the cross-phase applicability of data-driven diagnostic methods. This paper proposes a unified diagnosis method for inter-turn short-circuit faults in different phases under limited annotation conditions. [Methods] The phase-to-phase difference was regarded as a specific form of data distribution shift, so the core criterion for inter-turn short-circuit was independent of the specific phase. Based on this, a feasible method was proposed in this paper from the perspective of cross-phase transfer, which utilized only single-phase inter-turn short-circuit fault data for model training and directly applied it to fault diagnosis of other phases. This method achieved multi-phase inter-turn short-circuit fault identification under single-phase training conditions by constructing a physically consistent feature representation and employing a unified lightweight diagnostic model. [Results] The results indicated that, without the introduction of complex transfer structures or additional labeled data, the proposed method demonstrated high diagnostic accuracy on the training phase and maintained stable performance in different phase-to-phase inter-turn short-circuit fault diagnosis tasks, significantly enhancing the cross-phase generalization ability of fault diagnosis. [Conclusion] This study provides a concise and effective solution for reducing the dependence of the inter-turn short-circuit fault diagnosis model on multi-phase labeled data and enhancing the model’s generalizability in practical engineering scenarios, thus possessing high engineering practical value.

国家自然科学基金(62506241);辽宁省教育厅公共关系重点项目(LJ212410142079);辽宁省博士科研启动基金项目(2024-BS-097)