access icon openaccess Identification of ultra-high-frequency PD signals in gas-insulated switchgear based on moment features considering electromagnetic mode

This is an open access article published by the IET and CEPRI under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 30/04/2019, Accepted 28/08/2019, Revised 26/06/2019, Published 25/02/2020

The feature extraction and pattern recognition techniques are of great importance to assess the insulation condition of gas-insulated switchgear. In this work, the ultra-high-frequency partial discharge (PD) signals generated from four types of typical insulation defects are analysed using S-transform, and the greyscale image in time-frequency representation is divided into five regions according to the cutoff frequencies of TE m 1 modes. Then, the three low-order moments of every subregion are extracted and the feature selection is performed based on the J criterion. To confirm the effectiveness of selected moment features after considering the electromagnetic modes, the support vector machine, k-nearest neighbour and particle swarm-optimised extreme learning machine (ELM) are utilised to classify the type of PD, and they achieve the recognition accuracies of 92, 88.5 and 95%, respectively. In addition, the results show that the ELM offers good generalisation performance at the fastest learning and testing speeds, thus more suitable for a real-time PD detection.

Inspec keywords: pattern recognition; power engineering computing; learning (artificial intelligence); time-frequency analysis; partial discharge measurement; support vector machines; gas insulated switchgear; particle swarm optimisation; feature extraction

Other keywords: nearest neighbour; ultra-high-frequency PD signals; selected moment features; pattern recognition techniques; low-order moments; feature selection; feature extraction; insulation condition; time-frequency representation; ultra-high-frequency partial discharge signals; cutoff frequencies; typical insulation defects; real-time PD detection; gas-insulated switchgear; electromagnetic mode

Subjects: Other topics in statistics; Data handling techniques; Knowledge engineering techniques; Other topics in statistics; Power engineering computing; Switchgear; Dielectric breakdown and discharges; Charge measurement

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