周郑, 郭丽娜. 基于S变换和k-means聚类的输电线路故障识别[J]. 黄河水利职业技术学院学报, 2021, 33(1): 45-50. DOI: 10.13681/j.cnki.cn41-1282/tv.2021.01.011
    引用本文: 周郑, 郭丽娜. 基于S变换和k-means聚类的输电线路故障识别[J]. 黄河水利职业技术学院学报, 2021, 33(1): 45-50. DOI: 10.13681/j.cnki.cn41-1282/tv.2021.01.011
    Zhou Zheng, Guo Lina. Transmission Line Fault Identification Based on S Transform and k-means Clustering[J]. Journal of Yellow River Conservancy Technical Institute, 2021, 33(1): 45-50. DOI: 10.13681/j.cnki.cn41-1282/tv.2021.01.011
    Citation: Zhou Zheng, Guo Lina. Transmission Line Fault Identification Based on S Transform and k-means Clustering[J]. Journal of Yellow River Conservancy Technical Institute, 2021, 33(1): 45-50. DOI: 10.13681/j.cnki.cn41-1282/tv.2021.01.011

    基于S变换和k-means聚类的输电线路故障识别

    Transmission Line Fault Identification Based on S Transform and k-means Clustering

    • 摘要: 根据正常电路和故障电路特征电流存在的差异,提出基于S 变换和k-means 聚类的输电线路故障识别方法。 通过S 变换的方式,获取线路特征电流的故障特征量,应用熵权法计算出变换综合相对熵,找出线路之间的差异。然后,使用k-means 聚类的方法识别出故障线路。通过仿真试验验证,该故障识别方法准确率较高、适应性强。

       

      Abstract: According to the difference of typical current between normal circuit and fault circuit, based on S Transform and K-means clustering, it proposed the fault identification method of transmission line. By means of S transform, it obtained the fault characteristic of line typical current. By using the entropy weight method to calculate the comprehensive relative entropy and find out the difference of lines. Then, it used the K-means clustering method to identify the fault transmission lines. The simulation experiment results showed that the fault identification method had high accuracy and strong adaptability.

       

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