Enhanced Method for Localization of Partial Discharges in Oil-Filled Transformers Using Acoustic Emission Signals - Yasutomo Otake; Kunihiko Tajiri (International Journal of Prognostics and Health Management)
Accurate measurement of partial discharges (PD) in power transformers is crucial for fault identification and effective maintenance planning. Acoustic emission (AE) sensing, less susceptible to external electromagnetic interference, offers non-invasive PD detection. This paper investigates the relationship between AE detection intensity, PD source type, and distance using AE sensors. Corona discharges exhibited the strongest AE wave intensities, followed by creepage discharges and PD in bubbles. AE wave intensity varies significantly based on discharge propagation speed, medium, and discharge space volume. The study experimentally compared three Time Difference of Arrival (TDOA) calculation methods for localization: energy criterion, Generalized Cross-Correlation (GCC), and GCC with Phase Transformation (PHAT). The energy criterion excelled in distributed sensor setups, while GCC-PHAT was superior in centralized configurations. GCC-PHAT, effectively suppressing noise and reflections, consistently outperformed standard GCC in accuracy, even at low discharge intensities. These findings promise improved precision and effectiveness in power transformer maintenance diagnostics.