Partial discharge pattern recognition method for mine-used dry-type transformer

Abstract

In order to improve recognition accuracy of partial discharge pattern of mine-used dry-type transformer, a partial discharge pattern recognition method for mine-used dry-type transformer was proposed. Firstly, orthogonal matching pursuit algorithm is used to denoise original partial discharge signal, which can retain useful information of the original partial discharge signal to the greatest extent. Then, autoregressive coefficient features of the partial discharge signal after denoising are extracted by autoregressive model. Finally, the autoregressive coefficient features are input into random forest integrated classifier to recognize partial discharge pattern. The experimental result shows that average recognition accuracy of the method is 98%.

Keywords

• mine-used dry-type transformer
• partial discharge
• orthogonal matching pursuit
• autoregressive coefficient feature
• random forest integrated classifier