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The State Key Laboratory of Power Transmission Equipment and System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China





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Abstract Dissolved gas analysis DGA has been widely applied to diagnose internal faults in transformer insulation systems. However, the accuracy of DGA technique is limited because of the lack of positive correlation of the fault-identifying gases with faults found in power transformers. This paper presents a laboratory study on the correlation between oil dissolved gas formation and partial discharge PD statistical parameters. Canonical correlation analysis CCA is employed to explore the underlying correlation and to extract principal feature parameters and gases in the development of different PD defects. This study is aimed to provide more information in assisting the separation, classification and identification of PD defects, which might improve the existing transformer dissolved gas analysis DGA schemes. An application of a novel ratio method for discharge diagnosis is proposed. The evaluation of DGA data both in laboratory and actual transformers proves the effectiveness of the method and the correlation investigation. View Full-Text

Keywords: partial discharges; dissolved gas analysis; canonical correlation analysis; fault diagnosis partial discharges; dissolved gas analysis; canonical correlation analysis; fault diagnosis





Autor: Weigen Chen * , Xi Chen, Shangyi Peng and Jian Li

Fuente: http://mdpi.com/



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