Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm
Over the years, many studies have been conducted to measure, analyse and characterise (i.e. mainly on the negative return strokes) the lightning-generated electric field waveform for a better understanding and conception of the lightning phenomenon and processes. The characterisation also contrib...
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my.upm.eprints.1040722023-07-07T01:27:06Z http://psasir.upm.edu.my/id/eprint/104072/ Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm Abdul Haris, Faranadia Over the years, many studies have been conducted to measure, analyse and characterise (i.e. mainly on the negative return strokes) the lightning-generated electric field waveform for a better understanding and conception of the lightning phenomenon and processes. The characterisation also contributes to the lightning protection system and lightning location system development as these systems require measured and validated data of the negative lightning return stroke characteristics. Previous studies mostly performed the characterisation of the negative return strokes using a conventional method, namely manual observations. Nevertheless, this traditional method could compromise data analysis accuracy due to human errors. The processing time to analyse the data would also be longer, especially for larger sample sizes. Therefore, this study proposed an automated negative lightning return strokes characterisation using a Brute-Force search algorithm, mainly on seven parameters, i.e. on zero-topeak rise time, 10-to-90% rise time, zero-crossing time, slow front time, slow front amplitude relative to peak, fast transition 10-to-90% rise time, and width dE/dt pulse at half peak value. For this purpose, the lightning-generated electric field measurement under different seasonal periods, was conducted at the College of Engineering, Universiti Tenaga Nasional (UNITEN), Selangor, Malaysia using a previously researched small-scale prallel-plate antenna. The criteria for each of the negative lightning return strokes parameters were established and defined based on specific mathematical equations. Accordingly, the proposed Brute-Force search algorithm characterised the negative lightning return strokes parameters based on the seven parameters. A total of 206 negative lightning return strokes waveforms were analysed and automatically characterised using the proposed algorithm. Comparisons of different data, including the manual data (i.e. obtained through the conventional method), data (automated) from a previous study, and the automated data (i.e. obtained using the proposed algorithm), were also carried out by evaluating the percentage difference, arithmetic mean, and standard deviation. The statistical analysis showed a good agreement between manual and automated data on each parameter, with a percentage difference observed between 0.08% and 6.88%. Bland-Altman plots analysis also showed that most of the plotted data were within the threshold limits. The results suggest that the proposed algorithm can provide an efficient structure and procedure by reducing the processing time, minimising human error, and eliminating the nonuniformity among users while characterising the lightning negative return strokes. Furthermore, the small-scale parallel-plate antenna that has been tested under real lightning condition can be operated as a portable, lightweight, and easy-to-install device for a lightning measurement system. 2021-11 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/104072/1/FARANADIA%20BINTI%20ABDUL%20HARIS%20-%20IR.pdf Abdul Haris, Faranadia (2021) Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm. Doctoral thesis, Universiti Putra Malaysia. Lightning Atmospheric electricity |
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Lightning Atmospheric electricity Abdul Haris, Faranadia Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
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Over the years, many studies have been conducted to measure, analyse and
characterise (i.e. mainly on the negative return strokes) the lightning-generated
electric field waveform for a better understanding and conception of the lightning
phenomenon and processes. The characterisation also contributes to the
lightning protection system and lightning location system development as these
systems require measured and validated data of the negative lightning return
stroke characteristics. Previous studies mostly performed the characterisation of
the negative return strokes using a conventional method, namely manual
observations. Nevertheless, this traditional method could compromise data
analysis accuracy due to human errors. The processing time to analyse the data
would also be longer, especially for larger sample sizes. Therefore, this study
proposed an automated negative lightning return strokes characterisation using
a Brute-Force search algorithm, mainly on seven parameters, i.e. on zero-topeak
rise time, 10-to-90% rise time, zero-crossing time, slow front time, slow
front amplitude relative to peak, fast transition 10-to-90% rise time, and width
dE/dt pulse at half peak value. For this purpose, the lightning-generated electric
field measurement under different seasonal periods, was conducted at the
College of Engineering, Universiti Tenaga Nasional (UNITEN), Selangor,
Malaysia using a previously researched small-scale prallel-plate antenna. The
criteria for each of the negative lightning return strokes parameters were
established and defined based on specific mathematical equations. Accordingly,
the proposed Brute-Force search algorithm characterised the negative lightning
return strokes parameters based on the seven parameters. A total of 206
negative lightning return strokes waveforms were analysed and automatically
characterised using the proposed algorithm. Comparisons of different data, including the manual data (i.e. obtained through the conventional method), data
(automated) from a previous study, and the automated data (i.e. obtained using
the proposed algorithm), were also carried out by evaluating the percentage
difference, arithmetic mean, and standard deviation. The statistical analysis
showed a good agreement between manual and automated data on each
parameter, with a percentage difference observed between 0.08% and 6.88%.
Bland-Altman plots analysis also showed that most of the plotted data were
within the threshold limits. The results suggest that the proposed algorithm can
provide an efficient structure and procedure by reducing the processing time,
minimising human error, and eliminating the nonuniformity among users while
characterising the lightning negative return strokes. Furthermore, the small-scale
parallel-plate antenna that has been tested under real lightning condition can be
operated as a portable, lightweight, and easy-to-install device for a lightning
measurement system. |
format |
Thesis |
author |
Abdul Haris, Faranadia |
author_facet |
Abdul Haris, Faranadia |
author_sort |
Abdul Haris, Faranadia |
title |
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
title_short |
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
title_full |
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
title_fullStr |
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
title_full_unstemmed |
Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm |
title_sort |
improved criteria determination of an automated negative lightning return strokes characterisation using brute-force search algorithm |
publishDate |
2021 |
url |
http://psasir.upm.edu.my/id/eprint/104072/1/FARANADIA%20BINTI%20ABDUL%20HARIS%20-%20IR.pdf http://psasir.upm.edu.my/id/eprint/104072/ |
_version_ |
1772813447994540032 |