Scholarlink

<p>Inter Turn Fault (ITF) identification and location of faulty phases in Three-phase Transformer using Mystery Curves (MC) has been presented in this paper. The Insulation degradation among one or more successive turns of the winding causes ITF, when the fault is not acknowledged, it proliferates to the adjacent turns of the winding and results in permanent damage to the winding. The MC approach is valuable tool in condition monitoring of transformers, enabling early detection of ITF allowing proactive scheduling and preventing unexpected failures. This approach initially computes the analytic signal of the real valued input signals utilizing the Hilbert Transform (HT). Through representing the polar form of such a signal which is recognized as magnitude and frequency variations distinct MC patterns can be discovered. The deviations in the MC views from the normal curve shape over time can indicate the ITF occurrence. In addition, the Phase-angle Variation Response (PVR) of MC locates the faulty phase of transformer winding precisely. The experimental investigations used for the validation of this novel approach identifies the ITF on the transformer currents successfully regardless of the fault levels. Compared to traditional fault detection methods, the proposed approach outperforms threshold-based strategies, simple, easy to visualize facilitating quick decision making, quantifiable indication of fault severity and reducing the need of extensive signal processing expertise.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Application of Mystery Curves for Identification of Inter Turn Faults on a Three Phase Transformer

  • 期刊论文

  • 发表日期：

    2025年7月3日

查看全文
  • N. Ramesh,
  • S. Deepa,
  • P. Vanaja Ranjan

摘要

Inter Turn Fault (ITF) identification and location of faulty phases in Three-phase Transformer using Mystery Curves (MC) has been presented in this paper. The Insulation degradation among one or more successive turns of the winding causes ITF, when the fault is not acknowledged, it proliferates to the adjacent turns of the winding and results in permanent damage to the winding. The MC approach is valuable tool in condition monitoring of transformers, enabling early detection of ITF allowing proactive scheduling and preventing unexpected failures. This approach initially computes the analytic signal of the real valued input signals utilizing the Hilbert Transform (HT). Through representing the polar form of such a signal which is recognized as magnitude and frequency variations distinct MC patterns can be discovered. The deviations in the MC views from the normal curve shape over time can indicate the ITF occurrence. In addition, the Phase-angle Variation Response (PVR) of MC locates the faulty phase of transformer winding precisely. The experimental investigations used for the validation of this novel approach identifies the ITF on the transformer currents successfully regardless of the fault levels. Compared to traditional fault detection methods, the proposed approach outperforms threshold-based strategies, simple, easy to visualize facilitating quick decision making, quantifiable indication of fault severity and reducing the need of extensive signal processing expertise.