Application possibilities of artificial neural networks for recognizing partial discharges measured by the acoustic emission method

Abstract

The genesis of the research work presented in this paper constitutes the issue of the effective and efficient recognition of single-source one-time partial discharge forms that can occur in insulation systems of power transformers. The paper presents research results referring to the use of single-direction artificial neural networks for recognizing basic partial discharge forms that can occur in paper-oil insulation impaired by aging processes. The research work results presented show the recognition effectiveness of basic partial discharge forms depending on the descriptor of the analysis of the acoustic emission signal analysis. The detailed cognitive aim was selection of input parameters and an artificial neural network which would be the best, considering recognition effectiveness and processing time, and which could be used as a classifier in an expert diagnostic system making identification of partial discharges measured by using the acoustic method possible.Index Terms -Partial discharge, paper-oil insulation, acoustics emission method, artificial neuron network, power transformer.

Analysis of Interference Signals Generated by Vibroacoustic Vibrations of Transformer Cores

“…The measurement chain consists of the following elements: wideband measurement transducer WD, type AH 17, preamplier type 2/4/6 from PAC, broadband amplier of type AE2A, a 12-bit measurement card type CH-3160, and industry PC. Detailed description of the measurement chain and the procedures used for processing and analyzing the recorded signals are presented in [1,7,10]. …”

A New Reliable Algorithm for Identifying Types of Partial Discharge Detected through Ultrasonic Emission

“…For this reason, detecting partial discharge is useful for the insulation assessment and to predict the life of the insulation [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”

“…The non-contact method usually uses chemical transformation, gas pressure, heat, light and acoustic emission. However, only the last two are considered as practically important [15]. In order to provide the accurate solution, it is vital to identify the PD type first.…”

Diagnosis of the Non-Concurrent Operation of the On-Load Tap Changer Contacts by the Acoustic Emission Method

“…The application of the acoustic emission method for the diagnosis of power transformers makes it possible to assess the technical condition of these appliances during their regular live operation, which is, undoubtedly, its advantage (Boczar et al, 2009;Cichoń, 2009;Kundu et al, 2008;Skubis et al, 2009). The essential application of this method is the possibility of detection of partial discharges occurring in the internal insulation system of the appliance.…”