Processing of partial discharge ultra-high frequency signals from a true size transformer

Quite a few methods have been proposed to detect partial discharge in power transformers, such as dissolved gas analysis (DGA), pulse current method, ultrasonic wave method and ultra-high frequency (UHF) method. UHF method, is widely used in condition monitoring recently for the sake of its wider spectrum and higher sensitivity. This paper presents a PD detection experiment inside a true size transformer which was rebuilt to install 9 UHF sensors. Four types of PD sources were placed into in the transformer. The pattern and intensity of PD can be changed by adjusting PD voltage and insulation distance. Signals detected by the sensors were decomposed and reconstructed by methods of Continuous Wavelet Transform (CWT) and Multi-Resolution Analysis (MRA) based on different wavelets. The time-frequency characteristic and de-noising performance of different transforms applying to PD signals were compared and the result shows that different transforms reflect advantages in different respects. A new method is proposed to extract PD signals from noises.