Abstract

Partial discharge (PD) location techniques are a useful tool for condition monitoring of electrical apparatus in power systems. However, the noisy PD measurements may significantly degrade the performance of location algorithms. This article deals with the PD location problem by using adaptive filtering techniques. Heretofore, scarce literature focuses on addressing the PD location based on such method. A novel adaptive algorithm, termed as total least-squares (TLS)-Matérn kernel (TLS-MK), is proposed. Benefiting from the merits of the Matérn kernel, the TLS model can effectively suppress the noise from the direct and reflected waves of the PD source. Meanwhile, the TLS-MK algorithm is used to estimate the time difference, which is used in the PD location. Moreover, the convergence behavior of the TLS-MK algorithm is analyzed. Simulations and experiments show that the proposed algorithm can enhance the location accuracy as compared to state-of-the-art methods for various PD signals.

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