Comparative Study of Extension Mode Method in Reducing Border Distortion Effect for Transient Voltage Disturbance

Asman, Saidatul Habsah; Abidin, Ahmad Farid

doi:10.11591/ijeecs.v6.i3.pp628-637

Cited by 7 publications

(7 citation statements)

References 14 publications

(2 reference statements)

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“…At the end of the signal, the convoluting window extends partially on the signal domain, in which abnormal coefficients arise and corrupted the transform. However, the distorted border gives significant influence that leads to situation of false indication [23][24][25][26]. Therefore, the threshold value was implemented for normal waveform to truncate the unwanted border distortion.…”

Section: Statistical Resultsmentioning

confidence: 99%

Determination of Different Fault Features in Power Distribution System Based on Wavelet Transform

Asman*,

Aziz,

Kadir

et al. 2019

IJRTE

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Nowadays, there are various signal processing methods that have been studied by many researchers in order to detect faults in power lines. From previous literature, signal processing that works based on time frequency analysis has been proven to accurately detect faults at high speed. In this study, wavelet transform is adopted to analyse fault occurrences on power line of distribution network. Three types of faults due to lightning, switching and short circuit fault were analysed based on their voltage waveform profiles. ‘Daubechies’ 4 (db4) mother wavelet and four levels decomposition were implemented to extract the features. Approximation at level 4 (A4) and detail coefficient at level 1 to 4 (D1-D4) were extracted to evaluate the energy, skewness, and kurtosis. Based on the results, lightning showed the highest energy, skewness and kurtosis compared to the short circuit and switching voltage waveform. Therefore, these features can be utilized as the new parameters for fault detection in a power system network

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Section: Statistical Resultsmentioning

confidence: 99%

Determination of Different Fault Features in Power Distribution System Based on Wavelet Transform

Asman*,

Aziz,

Kadir

et al. 2019

IJRTE

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“…It has been employed to each level of decomposition process to get perfect reconstruction. Previously, S.Habsah et al [4] had employed extension mode method to reduce the border for non-stationary finite length signal and discovered that smooth padding yielded satisfying result. In this paper, three basic extension mode will be employed to identify its effectiveness on minimizing border distortion effect when sliding window signal is hired.…”

Section: Extension Mode Theorymentioning

confidence: 99%

“…The evolution of signal processing tools namely wavelet transform overcoming conventional Fourier analysis's drawback which can perfectly localize signal in frequency domain but failing in time domain [3]. The capability of wavelet in recognizing indexed in waveform make it well perform to extract features for gaining amplitude and frequency information [4]. It has the ability to classify types of power disturbances based on duration of harmonic content in the signal.…”

Section: Introductionmentioning

confidence: 99%

“…Thus the most appropriate extension mode should be chosen based on the requirement. Habsah et al [4] revealed that smooth-padding mode is the best extension mode to reduce border effect for transient and voltage sag signal. Those researcher cover only for finite length signal to reduce the border.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, this paper is organized to identify the effect of border distortion after extension mode implementation at sliding window wavelet signal. The proposed technique is being compared with conventional technique [4]. The signal is simulated in Matlab 2017a prompt and Matlab Toolbox.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extension Mode in Sliding Window Technique to Minimize Border Distortion Effect

Asman¹,

Abidin²,

Dahlan³

2017

IJEECS

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This paper deals with border distortion effect at starting and ending of finite signal by proposing sliding window technique and basic extension mode implementation. Single phase of transient and voltage sag is chosen to be analyzed in wavelet. The signal which being used for the analysis is simulated in Matlab 2017a. Disturbance signal decomposes into four level and Daubechies 4 (db4) has been chosen for computation. The proposed technique has been compared with conventional method which is finite length power disturbance analysis. Simulation result revealed that the proposed smooth-padding mode can be successfully minimized the border distortion effect compared to the zero-padding and symmetrization approach.

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Identification of transient overvoltage using discrete wavelet transform with minimised border distortion effect and support vector machine

Asman

Abidin

Yusoh

et al. 2022

Results in Engineering

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Comparative Study of Extension Mode Method in Reducing Border Distortion Effect for Transient Voltage Disturbance

Abstract: Wavelet transform is an essential method for preprocessing and analyzing non

Cited by 7 publications

References 14 publications

Determination of Different Fault Features in Power Distribution System Based on Wavelet Transform

Determination of Different Fault Features in Power Distribution System Based on Wavelet Transform

Extension Mode in Sliding Window Technique to Minimize Border Distortion Effect

Identification of transient overvoltage using discrete wavelet transform with minimised border distortion effect and support vector machine

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