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Determination of accuracy of winding deformation method using kNN based classifier used for 3 MVA transformer

机译:使用KNN基于3MVA变压器的基于KNN的分类器测定绕组变形方法的准确性

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This paper presents a detecting system on power transformer in transformer winding, core and on load tap changer (OLTC). Accuracy of winding deformation is determined using kNN based classifier. Winding deformation in power transformer can be measured using sweep frequency response analysis (SFRA), which can enhance the diagnosis accuracy to a large degree. It is suggested that in the results minor deformation faults can be detected at frequency range of 1 mHz to 2 MHz. The values of RCL parameters are changed when faults occur and hence frequency response of the winding will change accordingly. The SFRA data of tested transformer is compared with reference trace. The difference between two graphs indicate faults in the transformer. The deformation between 1 mHz to 1kHz gives winding deformation, 1 kHz to 100 kHz gives core deformation and 100 kHz to 2 MHz gives OLTC deformation.
机译:本文介绍了变压器绕组,核心和负载分接开关(OLTC)的电力变压器检测系统。使用基于KNN的分类器确定绕组变形的精度。可以使用扫描频率响应分析(SFRA)测量电力变压器中的绕组变形,可以在很大程度上提高诊断精度。建议在结果中,可以在1MHz至2MHz的频率范围内检测次要变形故障。当发生故障时,RCL参数的值发生变化,因此绕组的频率响应会相应地改变。将测试变压器的SFRA数据与参考迹线进行比较。两个图之间的差异表示变压器中的故障。 1 MHz至1kHz之间的变形给出绕组变形,1kHz至100 kHz给出核心变形,100 kHz至2 MHz给出了OLTC变形。

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