Maximum Likelihood-based Technique for Accurate Estimation of Time-delay between UHF Signals Radiated from Partial Discharge Sources

Abstract

One of the useful way for localization of partial discharge (PD) sources inside any electrical substation is the use of multiple ultra-high frequency (UHF) sensors. UHF signals radiated from any PD source can travel a longer distance and can be captured by the multiple UHF sensors placed around the substations. The localization of PD sources is done primarily by calculating the time delays between the impulsive signals received at the UHF sensors.However, the time delay estimation is very challenging in the presence of interference of other Electro-Magnetic signals. In the present work, several time domain and frequency domain based techniques have been investigated and applied on several PD signals captured from the different air-insulated substation in India. Various time-domain based techniques that have been applied are the first peak (FP), cross-correlation (CC), and cumulative energy (CE). The frequency-domain based Generalized Cross Correlation (GCC) technique has also been applied with their different weighing functions such are the Phase Transform (PHAT), Smoothed Coherence Transform (SCOT), Maximum Likelihood estimator and the Eckart Filter (EF). From the experimental result, it is observed that the GCC with ML estimator provide the most suitable result across different experimental conditions.