Proceedings ArticleDOI
Wavelet based transmission line fault analysis: A literature survey
Sundaravaradan Navalpakkam Ananthan,P. Rajaraman,D Suzith,M Dilip Kumar,G Abilash,M. Jaya Bharata Reddy,Dusmanta Kumar Mohanta +6 more
- pp 254-259
TLDR
A comprehensive review of the techniques employed in fault analysis which have evolved over the last decade is presented in this article, which mainly focuses on the implementation of discrete wavelet transform (WT), multi-resolution analysis (MRA) artificial neural networks (ANN) and fuzzy logic for fault analysis.Abstract:
Transmission lines faults are an inevitable part of any power system. They cause a disruption in the power supply, which is undesirable. With an ever-increasing demand for better performance and minimal interruptions, accurate fault analysis is necessary to restore a system to its normal operation by detecting and clearing the transmission line fault. This paper presents a comprehensive review of the techniques employed in fault analysis which have evolved over the last decade. This review paper mainly focuses on the implementation of discrete wavelet transform (WT), multi-resolution analysis (MRA) artificial neural networks (ANN) and fuzzy logic for fault analysis.read more
Citations
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Journal ArticleDOI
Discrete wavelet transform optimal parameters estimation for arc fault detection in low-voltage residential power networks
TL;DR: In this paper, an in-depth analysis providing the optimal parameters estimation for discrete wavelet transform (DWT) applied to detection of series arc faults in the household AC power network is presented The influence of three parameters investigated: the choice of mother wavelet, level of decomposition and sampling frequency.
Journal ArticleDOI
ArcNet: Series AC Arc Fault Detection Based on Raw Current and Convolutional Neural Network
TL;DR: In this paper, a convolutional neural network-based arc detection model named ArcNet was proposed, which achieved an average runtime of 31 ms/sample of 1 cycle at 10 kHz sampling rate, which proves the feasibility of practical hardware deployment for realtime processing.
Journal ArticleDOI
ArcNet: Series AC Arc Fault Detection Based on Raw Current and Convolutional Neural Network
TL;DR: In this article , a convolutional neural network-based arc detection model named ArcNet was proposed, which achieved an average runtime of 31 ms/sample of 1 cycle at 10 kHz sampling rate, which proves the feasibility of practical hardware deployment for realtime processing.
Proceedings ArticleDOI
A wavelet based novel technique for detection and classification of parallel transmission line faults
Sundaravaradan Navalpakkam Ananthan,Rounak Meyur,P. Rajaraman,Balimidi Mallikarjuna,M. Jaya Bharata Reddy,Dusmanta Kumar Mohanta +5 more
TL;DR: The reliability of this algorithm has been tested using a MATLAB/Simulink model of a parallel transmission line for a variety of faults, fault distances and fault inception angles and this validates the proposed digital relaying technique.
Journal ArticleDOI
Robust functional analysis for fault detection in power transmission lines
TL;DR: In this paper, the authors proposed robust functional analysis of power transmission lines to represent the behavior of the electrical signals and to estimate the upper and lower limits under normal operating conditions, but the results showed that the estimation is biased and relies on statistical assumptions that do not hold in practice.
References
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Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Journal ArticleDOI
Fault location using wavelets
F.H. Magnago,Ali Abur +1 more
TL;DR: In this article, the use of wavelet transforms for analyzing power system fault transients in order to determine the fault location is described, which is related to the travel time of the signals which are already decomposed into their modal components.
Journal ArticleDOI
Wavelets and electromagnetic power system transients
TL;DR: The wavelet transform was introduced as a method for analyzing electromagnetic transients associated with power system faults and switching as mentioned in this paper, and it is more appropriate than the familiar Fourier methods for the nonperiodic, wide-band signals associated with EM transients.
Journal ArticleDOI
Fault detection and classification in transmission lines based on wavelet transform and ANN
TL;DR: In this article, the fault detection and its clearing time are determined based on a set of rules obtained from the current waveform analysis in time and wavelet domains, which is able to single out faults from other power quality disturbances, such as voltage sags and oscillatory transients, which are common in power systems operation.
Journal ArticleDOI
Wavelets for the analysis and compression of power system disturbances
Tim Littler,D.J. Morrow +1 more
TL;DR: In this paper, the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms were evaluated using an actual power system disturbance from a digital fault recorder and the application of wavelet compression in power monitoring to mitigate against data communications overheads.