PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization

Partial discharge (PD) source location using acoustic emission (AE) is widely utilized by many transformer manufacturers and power utility engineers in routine and critical situation for optimal operation of the electrical power system as well as further risk management and repair planning. The PD d...

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Main Authors: K. Meka, A. V. Giridhar, D. V. S. S. Siva Sarma
Format: Article
Language:English
Published: Spolecnost pro radioelektronicke inzenyrstvi 2018-12-01
Series:Radioengineering
Subjects:
Online Access:https://www.radioeng.cz/fulltexts/2018/18_04_1119_1127.pdf
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spelling doaj-d2d6b4d5224d42a0b434a9554b0bf04c2020-11-24T20:53:34ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122018-12-0127411191127PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm OptimizationK. MekaA. V. GiridharD. V. S. S. Siva SarmaPartial discharge (PD) source location using acoustic emission (AE) is widely utilized by many transformer manufacturers and power utility engineers in routine and critical situation for optimal operation of the electrical power system as well as further risk management and repair planning. The PD detection is not enough to take solution, so identification of PD source is essential to restore apparatus condition. This work aim is to localize the defect geometrically by means of TDOA (time difference of arrival) signals from the sensors fixed on the power transformer. The solution for PD source location is acquired by making these nonlinear equations as optimization problem. In this technique, the inertia weight is effec-tively regulated by using 49 and 9 simple IF-THEN fuzzy rules to improve the global optimal solution and impairs the local convergence problem and improves the accuracy in estimating the PD source location. The simulation results reveal that PD location accuracy with minimum of maximum deviation error, absolute error and relative error is better when compared to other constant parameter intelligent methods which were reported in the literature.https://www.radioeng.cz/fulltexts/2018/18_04_1119_1127.pdfAcoustic emissionpartial dischargefuzzy adaptive particle swarm optimizationfuzzy rulessource localization
collection DOAJ
language English
format Article
sources DOAJ
author K. Meka
A. V. Giridhar
D. V. S. S. Siva Sarma
spellingShingle K. Meka
A. V. Giridhar
D. V. S. S. Siva Sarma
PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
Radioengineering
Acoustic emission
partial discharge
fuzzy adaptive particle swarm optimization
fuzzy rules
source localization
author_facet K. Meka
A. V. Giridhar
D. V. S. S. Siva Sarma
author_sort K. Meka
title PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
title_short PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
title_full PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
title_fullStr PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
title_full_unstemmed PD Source Location Utilizing Acoustic TDOA Signals in Power Transformer by Fuzzy Adaptive Particle Swarm Optimization
title_sort pd source location utilizing acoustic tdoa signals in power transformer by fuzzy adaptive particle swarm optimization
publisher Spolecnost pro radioelektronicke inzenyrstvi
series Radioengineering
issn 1210-2512
publishDate 2018-12-01
description Partial discharge (PD) source location using acoustic emission (AE) is widely utilized by many transformer manufacturers and power utility engineers in routine and critical situation for optimal operation of the electrical power system as well as further risk management and repair planning. The PD detection is not enough to take solution, so identification of PD source is essential to restore apparatus condition. This work aim is to localize the defect geometrically by means of TDOA (time difference of arrival) signals from the sensors fixed on the power transformer. The solution for PD source location is acquired by making these nonlinear equations as optimization problem. In this technique, the inertia weight is effec-tively regulated by using 49 and 9 simple IF-THEN fuzzy rules to improve the global optimal solution and impairs the local convergence problem and improves the accuracy in estimating the PD source location. The simulation results reveal that PD location accuracy with minimum of maximum deviation error, absolute error and relative error is better when compared to other constant parameter intelligent methods which were reported in the literature.
topic Acoustic emission
partial discharge
fuzzy adaptive particle swarm optimization
fuzzy rules
source localization
url https://www.radioeng.cz/fulltexts/2018/18_04_1119_1127.pdf
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