Analyzing the electromagnetic waves generated by partial discharges is effective to assess insulation degeneration. In this paper, we describe a locating method for a partial discharge source based on maximum likelihood estimation. This method uses the root mean square and the direction of arrival of partial discharge signals which are calculated from measurement data obtained using sensors. This information is integrated using the maximum likelihood method. In this case, only the signals received in a good reception condition are used because the signals affected by multipath effects can decrease the estimation accuracy. This paper considers the case that apparatuses interrupt the direct paths from a partial discharge source to sensors. The capability of the proposed method was confirmed by simulations using the finite difference time domain method. The results include the comparison of performance for the number of sensors and show that this method has enough resolution to detect partial discharge sources. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
[1]
Martin D. Judd.
Using finite difference time domain techniques to model electrical discharge phenomena
,
2000,
2000 Annual Report Conference on Electrical Insulation and Dielectric Phenomena (Cat. No.00CH37132).
[2]
Feng Zhao,et al.
Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks
,
2002,
Int. J. High Perform. Comput. Appl..
[3]
M.D. Judd,et al.
Partial discharge monitoring for power transformer using UHF sensors. Part 2: field experience
,
2005,
IEEE Electrical Insulation Magazine.
[4]
P.J. Moore,et al.
RF-Based Partial Discharge Early Warning System for Air-Insulated Substations
,
2009,
IEEE Transactions on Power Delivery.
[5]
Katsuo Isaka,et al.
Estimation of the Number of Partial Discharge Sources Using Multichannel Blind Deconvolution of Electromagnetic Waves
,
2008
.