Automatic partial discharge recognition using the cross wavelet transform in high voltage cable joint measuring systems using two opposite polarity sensors. (May 2020) - Rodrigo Mor, A.; Muñoz, F.A.; Wu, J.; Castro Heredia, L.C.
Highlights: A new wavelet application based on cross wavelet transform (XWT) was investigated and deployed. PD pulses were measured in a high voltage (HV) cable system, during impulse and superimposed voltages. In the experiments, 51, 898 signals were acquired, in which 733 were PD signals from the joint and 51, 165 corresponded to noise or pulse shaped external disturbances. The XWT analysis has been proven to be an useful tool in this particular application to identify PD pulses from the cable joint. Abstract: This paper presents a new wavelet analysis approach in partial discharges cable joint measurements in noisy environments. The proposed technique uses the Cross Wavelet Transform (XWT) to separate PD signals from noise and external disturbances in partial discharges measurements in cable joints using two opposite polarity sensors. The partial discharge measurements were performed during impulse and superimposed voltages, leading to a huge amount of noise and pulse shaped external disturbances. The XWT foundations, the experimental setup and the XWT methodology proposed are presented together with the results of the recognition of PD originated in the cable joint. In the experiments, 51, 898 signals were acquired, in which 733 were PD signals from the joint and 51, 165 corresponded to noise or external disturbances. The XWT performance was studied, finding that 97% of the PD signals were correctly separated by the technique proposed. The results demonstrate the effectivity of the XWT in separating PD signals from noise and external disturbances in this particular measuring system configuration.