A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation

Single Perceptron Smart Sensor (SPSS) is a new Ultra-High Frequency (UHF) sensor developed to significantly improve the pre-fault monitoring system for early detection, localization, and identification of the Corona and Arcs Electric Discharges (EDs) in an indoor substation. Corona and Arcs ED const...

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主要作者:	Lorothy, Morrison Buah Singkang
格式:	Thesis
語言:	English English English
出版:	2024
主題:	TK Electrical engineering Electronics Nuclear engineering
在線閱讀:	http://ir.unimas.my/id/eprint/45389/3/DOW_Lorothy%20anak%20Morrison%20Buah.pdf http://ir.unimas.my/id/eprint/45389/4/Thesis%20PhD_Lorothy%20Morrison%20Buah%20-%2024%20pages.pdf http://ir.unimas.my/id/eprint/45389/5/Thesis%20PhD_Lorothy%20Morrison%20Buah.ftext.pdf
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id	my-unimas-ir.45389
record_format	uketd_dc
spelling	my-unimas-ir.453892024-08-13T00:19:13Z A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation 2024-07-26 Lorothy, Morrison Buah Singkang TK Electrical engineering. Electronics Nuclear engineering Single Perceptron Smart Sensor (SPSS) is a new Ultra-High Frequency (UHF) sensor developed to significantly improve the pre-fault monitoring system for early detection, localization, and identification of the Corona and Arcs Electric Discharges (EDs) in an indoor substation. Corona and Arcs ED constitute a significant threat to electrical safety, the apparatus, and the stability of a power system due to the aging and material degradation in the power apparatus. Hence, an early preventive approach must be performed effectively for pre-fault threat detection. In this research, a novel pre-fault monitoring system utilizing SPSS is developed, embedding a novel Signal Identifier Technique for the Corona and Arcs ED detection, localization, and identification. The SPSS formation integrates a 2-element Linear Array Antenna with a Single Perceptron-Artificial Neural Network (SP-ANN). It detects and localizes the Corona and Arc ED signals based on the Direction of Arrival (DOA) angle. The SP-ANN utilizes a single-layer neuron with less complexity, speedy detection, and localization within seconds. The waveform-based signal feature extraction uses the Signal Identifier Technique for signal identification. Since the frequency range of the Corona and Arcs is undecidable, the accuracy of the pre-fault monitoring is tested for the Corona and Arcs ED at a sampling frequency of 300 MHz to 3 GHz. The SPSS has revealed an accuracy of 99.86% for signal identification with minimal computational complexity, thus giving another practical wireless technique for UHF signal interpretation. University Malaysia Sarawak 2024-07 Thesis http://ir.unimas.my/id/eprint/45389/ http://ir.unimas.my/id/eprint/45389/3/DOW_Lorothy%20anak%20Morrison%20Buah.pdf text en staffonly http://ir.unimas.my/id/eprint/45389/4/Thesis%20PhD_Lorothy%20Morrison%20Buah%20-%2024%20pages.pdf text en public http://ir.unimas.my/id/eprint/45389/5/Thesis%20PhD_Lorothy%20Morrison%20Buah.ftext.pdf text en validuser phd doctoral University Malaysia Sarawak Faculty of Engineering
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English English English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Lorothy, Morrison Buah Singkang A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
description	Single Perceptron Smart Sensor (SPSS) is a new Ultra-High Frequency (UHF) sensor developed to significantly improve the pre-fault monitoring system for early detection, localization, and identification of the Corona and Arcs Electric Discharges (EDs) in an indoor substation. Corona and Arcs ED constitute a significant threat to electrical safety, the apparatus, and the stability of a power system due to the aging and material degradation in the power apparatus. Hence, an early preventive approach must be performed effectively for pre-fault threat detection. In this research, a novel pre-fault monitoring system utilizing SPSS is developed, embedding a novel Signal Identifier Technique for the Corona and Arcs ED detection, localization, and identification. The SPSS formation integrates a 2-element Linear Array Antenna with a Single Perceptron-Artificial Neural Network (SP-ANN). It detects and localizes the Corona and Arc ED signals based on the Direction of Arrival (DOA) angle. The SP-ANN utilizes a single-layer neuron with less complexity, speedy detection, and localization within seconds. The waveform-based signal feature extraction uses the Signal Identifier Technique for signal identification. Since the frequency range of the Corona and Arcs is undecidable, the accuracy of the pre-fault monitoring is tested for the Corona and Arcs ED at a sampling frequency of 300 MHz to 3 GHz. The SPSS has revealed an accuracy of 99.86% for signal identification with minimal computational complexity, thus giving another practical wireless technique for UHF signal interpretation.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Lorothy, Morrison Buah Singkang
author_facet	Lorothy, Morrison Buah Singkang
author_sort	Lorothy, Morrison Buah Singkang
title	A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
title_short	A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
title_full	A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
title_fullStr	A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
title_full_unstemmed	A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation
title_sort	single perceptron smart sensor technique for pre-fault monitoring system in an indoor substation
granting_institution	University Malaysia Sarawak
granting_department	Faculty of Engineering
publishDate	2024
url	http://ir.unimas.my/id/eprint/45389/3/DOW_Lorothy%20anak%20Morrison%20Buah.pdf http://ir.unimas.my/id/eprint/45389/4/Thesis%20PhD_Lorothy%20Morrison%20Buah%20-%2024%20pages.pdf http://ir.unimas.my/id/eprint/45389/5/Thesis%20PhD_Lorothy%20Morrison%20Buah.ftext.pdf
_version_	1811771574568615936

A Single Perceptron Smart Sensor Technique for Pre-fault Monitoring System in an Indoor Substation

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