论文信息 - Feature Analysis of Numerical Calculated Data from Sweep Frequency Analysis (SFRA) Traces Using Self Organizing Maps

Feature Analysis of Numerical Calculated Data from Sweep Frequency Analysis (SFRA) Traces Using Self Organizing Maps

This paper presents a comprehensive investigation of the Self Organizing Map (SOM) classification process of good and defective power distribution transformers. Three main features were extracted from the numerical calculation method of the Sweep Frequency Response Analysis (SFRA) signals acquired from the transformers. These features are the input vectors for the SOM classification. Analysis of the results has shown the capability of the features and the SOM classification method to differentiate between good and defective transformers.

[1] M. de Nigris,et al. APPLICATION OF MODERN TECHNIQUES FOR THE CONDITION ASSESSMENT OF POWER TRANSFORMERS , 2004 .

[2] Pradeep M. Nirgude,et al. Application of numerical evaluation techniques for interpreting frequency response measurements in power transformers , 2008 .

[3] A. Kraetge,et al. Aspects of the Practical Application of Sweep Frequency Response Analysis (SFRA) on Power Transformers , 2009 .

[4] C. Senabre,et al. Classification, Filtering, and Identification of Electrical Customer Load Patterns Through the Use of Self-Organizing Maps , 2006, IEEE Transactions on Power Systems.