The measurement of partial discharges (PD) in power transformers is crucial for fault detection and maintenance scheduling. In this paper, the relationship between detection intensity, type of PD source and propagation distance is investigated using an acoustic emission (AE) sensor. The AE wave intensity by the corona discharges are relatively strong. Creeping discharges were next, followed by PD in bubbles. Furthermore, two methods for calculating time difference of arrival (TDOA) in locate calculations, energy reference and generalized cross-correlation (GCC), were experimentally compared. The results showed that the energy reference method is suitable when sensors can be placed around the tank, while the GCC method is suitable when sensors are concentrated in specific parts of the tank. This finding may contribute to improving the accuracy of maintenance diagnostics.
Transformer, maintenance, partial discharge, acoustic emittion, localization
Mirzaei, H., Akbari, A., Gackenbach, E., Zanjani, M., and Miralikhani, K., (2013) "A Novel Method for Ultra High Frequency Partial Discharge Localization in Power Transformers Using Particle Swarm Optimization Algorithm, IEEE Electrical Magazine, vol. 29, no. 2, pp. 26-39, doi: 10.1109/MEI.2013. 6457597.
Gao, C., Wang, W., Song, S., Wang, S., Yu, L., and Wang, Y., (2018) "Localization of partial discharge in transformer oil using Fabry-Pérot optical fiber sensor array," IEEE Transactions on Dielectrics and Electrical Insulation, vol. 25, no. 6, pp. 2279-2286, Dec. 2018, doi: 10.1109/TDEI.2018.007065.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.