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[摘要]
【目的】匝间短路是配电变压器最为频发的故障类型,轻微匝间短路未及时处置,则可能演化为严重匝间短路,危及变压器的稳定运行。本研究旨在探索一种能够有效识别轻微故障的高精度诊断方法,以实现早期预警。【方法】首先,针对早期短路工况,提出一种用非线性电弧特性替代短路点阻抗的方法,并通过高阻抗小电弧模拟变压器匝间早期短路,提取故障前后绕组电流的信号并分析磁通变化等。其次,提出了基于注意力机制的多尺度残差网络模型,实现了对匝间短路的高效识别。【结果】仿真与试验结果表明,采用非线性电弧阻抗仿真得到的故障电流远小于线性阻抗,匝间短路导致铁心与绕组间气隙的漏磁通密度增大,造成电磁损耗总体上升。本文所提方法能够有效区分正常运行、轻微匝间短路和严重匝间短路三种状态,测试准确率高达0.975。【结论】本研究可有效揭示变压器早期匝间短路的电磁响应特性,为故障早期检测提供了理论参考。
[Key word]
[Abstract]
[Objective] Inter-turn short circuit is the most frequent type of fault in distribution transformers, and if a minor inter-turn short circuit is not dealt with in time, it may evolve into a serious inter-turn short circuit, endangering the stable operation of the transformer. This study aims to explore a high-precision diagnostic method capable of effectively identifying incipient faults to achieve early warning. [Methods] Firstly, for the early short-circuit condition, a method using nonlinear arc characteristics to replace the impedance at the short-circuit point was proposed. A high-impedance, low-energy arc was used to simulate an incipient inter-turn short circuit in the transformer. The winding current signals before and after the fault were extracted, and the distortion characteristics of magnetic flux variation was analyzed. Subsequently, a multi-scale residual network model based on the attention mechanism was proposed, achieved efficient identification of interturn short-circuit faults. [Results] Simulation and experimental results indicated that the fault current obtained through nonlinear arc impedance simulation was significantly smaller than that from linear impedance simulation. The inter-turn short circuit led to an increase in the leakage flux density within the air gap between the core and the windings, resulted in an overall rise in electromagnetic losses. The method proposed in this paper was effectively able to distinguish between the three states: normal operation, minor inter-turn short circuit, and severe inter-turn short circuit, achieving a test accuracy of 0.975. [Conclusion] The research can effectively reveal the electromagnetic response characteristics of the transformer’s early inter-turn short circuit, and lay a theoretical reference for the early fault detection.
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