An Application Of Wavelet Transform In Acoustic Signal Extraction Of Partial Discharge

On-line Partial Discharge(PD) monitoring for HV power equipments is one of themost important techniques to maintain the reliability of power systems.However, thecurrent available PD measurements are not desirable enough to detect PD inequipment in service.The major problem is the strong coupling of various noises thatgreatly reduce the sensitivity of the measured PD and even prevent meaningfulmeasurements.A partial discharge (PD) activity in the power equipments generates acousticalwaves, which can be detected by acoustic sensor placed on the external surface ofpower equipments. The acoustic detection methods have advantages over the othermethods in that they are non-invasive and immune to electromagnetic noise. In thispaper an acoustic detecting instrument is used to collect the acoustic signals of PD,and the characteristics of these signals are analyzed. Since PD signal has strongsingularity, which can be used to effectively extract PD pulses from background noise.Wavelet transform has the outstanding property of extruding the local features of asignal in both time and frequency domain, so a de-noise algorithm based on wavelettransform is applied to extract acoustic signals of PD. In order to remove the slightinterferences, an algorithm of Teager's energy operators is used to strengthen the localenergy of signals and increases the PD signals to noise ratio in this paper. Simulationsand experiments show that the de-noised signals can be effectively obtained by thealgorithm.The results show that the algorithm not only increases the signal to noise ratio,but also preserves the energy and pulse amplitude.