A smart partial discharge classification SOM with optimized statistical transformation feature

Bohari, Zul Hasrizal and Isa, Muzamir and Abdullah, Ahmad Zaidi and Soh, Ping Jack and Sulaima, Mohamad Fani (2021) A smart partial discharge classification SOM with optimized statistical transformation feature. Bulletin of Electrical Engineering and Informatics, 10 (2). pp. 1054-1062. ISSN 2089-3191

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1. BEEI_A SMART PARTIAL DISCHARGE CLASSIFICATION SOM WITH OPTIMIZED STATISTICAL TRANSFORMATION FEATURE.PDF
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Official URL: https://beei.org/index.php/EEI/article/view/2751/2...

Abstract

Condition-based monitoring (CBM) has been a vital engineering method to assess high voltage (HV) equipment and power cables conditions or health levels. One of the effective CBM methods is partial discharge (PD) measurement or detection. PD event is the phenomenon that always associated with insulation healthiness. PD has been measured and evaluated in this paper to discriminate PD signals from a good signal. A mixed-signal being fed at an AI technique with statistical modified input data to do fast classification (less than five seconds) with nearly zero error. In this paper, an unsupervised neural network is applied for PD classification. The methods combine the self-organizing maps (SOMs) and feature statistical transformation. By the combination of these methods, the ‘range’ normalization method produced the best classification outcomes. This development decided that PD information was effectively correlated and grouped by means of MATLAB’s SOM Toolbox and transformation device to discriminate the normal signal from the PD signal.

Item Type:	Article
Uncontrolled Keywords:	Artificial intelligence, High voltage equipment, Partial discharge, Power cables, Self organizing maps, Statistical features, Transformation
Divisions:	Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Sabariah Ismail
Date Deposited:	11 Apr 2022 11:13
Last Modified:	21 Jul 2023 15:28
URI:	http://eprints.utem.edu.my/id/eprint/25806
Statistic Details:	View Download Statistic

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