In this paper, high-accuracy estimation of partial discharge (PD) location in an oil insulation system is addressed. The study aims at forming a fault-tolerant PD localization system. Initially, the algorithm periodically and probabilistically checks for possible bias in the acoustic emission sensors’ measurements. Once the detected bias is removed from the sensors’ measurements, multiple-model extended Kalman filters are used to estimate the location of the PD. The proposed multiple-model approach is intended to compensate for increased measurement noise statistics that result from sensor aging or ambient noise. The accuracy of the proposed algorithm is verified using multiple experimental results when the PD is initiated in different locations within the oil-filled transformer tank under different working conditions.
['Wasim M. F. Al-Masri', 'Mamoun F. Abdel-Hafez', 'Ayman H. El-Hag']
Toward High-Accuracy Estimation of Partial Discharge Location