Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction

Abdullah Akram Bajwa; Salman Habib; Muhammad Kamran

doi:10.1109/INMIC.2014.7097377

Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction

Abdullah Akram Bajwa
, Salman Habib
, Muhammad Kamran

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

2 Scopus citations

Abstract

Condition monitoring based on partial discharge diagnostics has seen a very rapid increase of interest from high voltage industry. Condition monitoring is an asset monitoring tool that can inform the user of real time health of their high voltage equipment / plant, which has now become a necessity in ageing networks that still have equipment in operation that has fulfilled its rated life. Partial discharge pulse detection and extraction is the first step of condition monitoring. This research is focused on assessing the capability of wavelet energy distribution for pulse extraction with the help of principle component analysis (PCA) and density based spatial clustering algorithm (DBSCAN). One problem that every pulse extraction method faces is that their efficiency is highly affected when a signal with high noise is processed through them. This research will also assess the robustness of the aforementioned procedure on signals with different signal to noise ratio by comparing results of each signal. Moreover, this procedure will also be vetted on its level of intrusiveness to see if it can be used for online condition monitoring.

Original language	English
Title of host publication	17th IEEE International Multi Topic Conference
Subtitle of host publication	Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings
Editors	Haroon Rasheed, Farah Lakhani, Mukesh Kumar Maheshwari
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	422-427
Number of pages	6
ISBN (Electronic)	9781479957545
DOIs	https://doi.org/10.1109/INMIC.2014.7097377
State	Published - 2014
Externally published	Yes
Event	17th IEEE International Multi Topic Conference, IEEE INMIC 2014 - Karachi, Pakistan Duration: 8 Dec 2014 → 10 Dec 2014

Publication series

Name	17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings

Conference

Conference	17th IEEE International Multi Topic Conference, IEEE INMIC 2014
Country/Territory	Pakistan
City	Karachi
Period	8/12/14 → 10/12/14

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

ASJC Scopus subject areas

General Computer Science
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/INMIC.2014.7097377

Cite this

Bajwa, A. A., Habib, S., & Kamran, M. (2014). Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction. In H. Rasheed, F. Lakhani, & M. K. Maheshwari (Eds.), 17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings (pp. 422-427). Article 7097377 (17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INMIC.2014.7097377

Bajwa, Abdullah Akram ; Habib, Salman ; Kamran, Muhammad. / Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction. 17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings. editor / Haroon Rasheed ; Farah Lakhani ; Mukesh Kumar Maheshwari. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 422-427 (17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings).

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title = "Wavelet energy distribution with PCA \& DBSCAN for partial discharge pulse extraction",

abstract = "Condition monitoring based on partial discharge diagnostics has seen a very rapid increase of interest from high voltage industry. Condition monitoring is an asset monitoring tool that can inform the user of real time health of their high voltage equipment / plant, which has now become a necessity in ageing networks that still have equipment in operation that has fulfilled its rated life. Partial discharge pulse detection and extraction is the first step of condition monitoring. This research is focused on assessing the capability of wavelet energy distribution for pulse extraction with the help of principle component analysis (PCA) and density based spatial clustering algorithm (DBSCAN). One problem that every pulse extraction method faces is that their efficiency is highly affected when a signal with high noise is processed through them. This research will also assess the robustness of the aforementioned procedure on signals with different signal to noise ratio by comparing results of each signal. Moreover, this procedure will also be vetted on its level of intrusiveness to see if it can be used for online condition monitoring.",

author = "Bajwa, \{Abdullah Akram\} and Salman Habib and Muhammad Kamran",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 17th IEEE International Multi Topic Conference, IEEE INMIC 2014 ; Conference date: 08-12-2014 Through 10-12-2014",

year = "2014",

doi = "10.1109/INMIC.2014.7097377",

language = "English",

series = "17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings",

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

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Bajwa, AA, Habib, S & Kamran, M 2014, Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction. in H Rasheed, F Lakhani & MK Maheshwari (eds), 17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings., 7097377, 17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 422-427, 17th IEEE International Multi Topic Conference, IEEE INMIC 2014, Karachi, Pakistan, 8/12/14. https://doi.org/10.1109/INMIC.2014.7097377

Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction. / Bajwa, Abdullah Akram; Habib, Salman; Kamran, Muhammad.
17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings. ed. / Haroon Rasheed; Farah Lakhani; Mukesh Kumar Maheshwari. Institute of Electrical and Electronics Engineers Inc., 2014. p. 422-427 7097377 (17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings).

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

TY - GEN

T1 - Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction

AU - Bajwa, Abdullah Akram

AU - Habib, Salman

AU - Kamran, Muhammad

PY - 2014

Y1 - 2014

N2 - Condition monitoring based on partial discharge diagnostics has seen a very rapid increase of interest from high voltage industry. Condition monitoring is an asset monitoring tool that can inform the user of real time health of their high voltage equipment / plant, which has now become a necessity in ageing networks that still have equipment in operation that has fulfilled its rated life. Partial discharge pulse detection and extraction is the first step of condition monitoring. This research is focused on assessing the capability of wavelet energy distribution for pulse extraction with the help of principle component analysis (PCA) and density based spatial clustering algorithm (DBSCAN). One problem that every pulse extraction method faces is that their efficiency is highly affected when a signal with high noise is processed through them. This research will also assess the robustness of the aforementioned procedure on signals with different signal to noise ratio by comparing results of each signal. Moreover, this procedure will also be vetted on its level of intrusiveness to see if it can be used for online condition monitoring.

AB - Condition monitoring based on partial discharge diagnostics has seen a very rapid increase of interest from high voltage industry. Condition monitoring is an asset monitoring tool that can inform the user of real time health of their high voltage equipment / plant, which has now become a necessity in ageing networks that still have equipment in operation that has fulfilled its rated life. Partial discharge pulse detection and extraction is the first step of condition monitoring. This research is focused on assessing the capability of wavelet energy distribution for pulse extraction with the help of principle component analysis (PCA) and density based spatial clustering algorithm (DBSCAN). One problem that every pulse extraction method faces is that their efficiency is highly affected when a signal with high noise is processed through them. This research will also assess the robustness of the aforementioned procedure on signals with different signal to noise ratio by comparing results of each signal. Moreover, this procedure will also be vetted on its level of intrusiveness to see if it can be used for online condition monitoring.

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M3 - Conference contribution

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 17th IEEE International Multi Topic Conference, IEEE INMIC 2014

Y2 - 8 December 2014 through 10 December 2014

ER -

Bajwa AA, Habib S, Kamran M. Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction. In Rasheed H, Lakhani F, Maheshwari MK, editors, 17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 422-427. 7097377. (17th IEEE International Multi Topic Conference: Collaborative and Sustainable Development of Technologies, IEEE INMIC 2014 - Proceedings). doi: 10.1109/INMIC.2014.7097377

Wavelet energy distribution with PCA & DBSCAN for partial discharge pulse extraction

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus subject areas

Access to Document

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Cite this