A Neural Network based power quality signal classification system using wavelet energy distribution

Praveen Sebastian; Pramod Antony Ds̈a

doi:10.1109/TAPENERGY.2015.7229617

A Neural Network based power quality signal classification system using wavelet energy distribution

Praveen Sebastian, Pramod Antony Ds̈a

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

This paper presents a method for the classification of common Power Quality(PQ) events. The described system for the characterization of disturbances is based on wavelet based feature extraction. The amount of data to be analyzed and how the data can be interpreted are of crucial importance in power quality analysis. Wavelet Transform(WT) has been widely used in power quality signal analysis. The advantage of wavelet transform is it can provide precise time information of power quality events and has many advantages over traditional signal analysis approaches. In this paper Discrete Wavelet Transform(DWT) is used for obtaining the energy distribution from simulated signals. The system is developed with Neural Network which is an effective tool in classification of signals in power systems.

Original language	English
Title of host publication	Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	199-204
Number of pages	6
ISBN (Electronic)	9781479982806
DOIs	https://doi.org/10.1109/TAPENERGY.2015.7229617
Publication status	Published - 01-01-2015
Externally published	Yes
Event	IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015 - Kollam, India Duration: 24-06-2015 → 26-06-2015

Conference

Conference	IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015
Country/Territory	India
City	Kollam
Period	24-06-15 → 26-06-15

All Science Journal Classification (ASJC) codes

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/TAPENERGY.2015.7229617

Cite this

Sebastian, P., & Ds̈a, P. A. (2015). A Neural Network based power quality signal classification system using wavelet energy distribution. In Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015 (pp. 199-204). [7229617] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TAPENERGY.2015.7229617

@inproceedings{80e11fb9eb854f3ab014170249f7722b,

title = "A Neural Network based power quality signal classification system using wavelet energy distribution",

abstract = "This paper presents a method for the classification of common Power Quality(PQ) events. The described system for the characterization of disturbances is based on wavelet based feature extraction. The amount of data to be analyzed and how the data can be interpreted are of crucial importance in power quality analysis. Wavelet Transform(WT) has been widely used in power quality signal analysis. The advantage of wavelet transform is it can provide precise time information of power quality events and has many advantages over traditional signal analysis approaches. In this paper Discrete Wavelet Transform(DWT) is used for obtaining the energy distribution from simulated signals. The system is developed with Neural Network which is an effective tool in classification of signals in power systems.",

author = "Praveen Sebastian and D{\"s}a, {Pramod Antony}",

year = "2015",

month = jan,

day = "1",

doi = "10.1109/TAPENERGY.2015.7229617",

language = "English",

pages = "199--204",

booktitle = "Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015 ; Conference date: 24-06-2015 Through 26-06-2015",

}

Sebastian, P & Ds̈a, PA 2015, A Neural Network based power quality signal classification system using wavelet energy distribution. in Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015., 7229617, Institute of Electrical and Electronics Engineers Inc., pp. 199-204, IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015, Kollam, India, 24-06-15. https://doi.org/10.1109/TAPENERGY.2015.7229617

A Neural Network based power quality signal classification system using wavelet energy distribution. / Sebastian, Praveen; Ds̈a, Pramod Antony.

Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 199-204 7229617.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Neural Network based power quality signal classification system using wavelet energy distribution

AU - Sebastian, Praveen

AU - Ds̈a, Pramod Antony

PY - 2015/1/1

Y1 - 2015/1/1

N2 - This paper presents a method for the classification of common Power Quality(PQ) events. The described system for the characterization of disturbances is based on wavelet based feature extraction. The amount of data to be analyzed and how the data can be interpreted are of crucial importance in power quality analysis. Wavelet Transform(WT) has been widely used in power quality signal analysis. The advantage of wavelet transform is it can provide precise time information of power quality events and has many advantages over traditional signal analysis approaches. In this paper Discrete Wavelet Transform(DWT) is used for obtaining the energy distribution from simulated signals. The system is developed with Neural Network which is an effective tool in classification of signals in power systems.

AB - This paper presents a method for the classification of common Power Quality(PQ) events. The described system for the characterization of disturbances is based on wavelet based feature extraction. The amount of data to be analyzed and how the data can be interpreted are of crucial importance in power quality analysis. Wavelet Transform(WT) has been widely used in power quality signal analysis. The advantage of wavelet transform is it can provide precise time information of power quality events and has many advantages over traditional signal analysis approaches. In this paper Discrete Wavelet Transform(DWT) is used for obtaining the energy distribution from simulated signals. The system is developed with Neural Network which is an effective tool in classification of signals in power systems.

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DO - 10.1109/TAPENERGY.2015.7229617

M3 - Conference contribution

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BT - Proceedings of IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - IEEE International Conference on Technological Advancements in Power and Energy, TAP Energy 2015

Y2 - 24 June 2015 through 26 June 2015

ER -

A Neural Network based power quality signal classification system using wavelet energy distribution

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