Automatic detection of power quality disturbances and identification of transient signals

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Many works involving detection and classification of power quality (PQ) events report the use of artificial neural network (ANN) to perform the classification task. No doubt, many have found ANN successfully performs the required task, but the approach requires a long training process and is too rigid if expansion or modification is desired. This paper proposes an alternative approach for the detection of PQ disturbances, which is simple, expandable and does not require training. The proposed system is built and tested using field-measured voltage waveforms, which are made of five types of PQ disturbances, namely, impulsive transient, oscillatory transient, single notch, repetitive notch and voltage sag. It perfectly detects and categorizes all test frames as either «clean» or «not clean», in which the frame labeled as «not clean» consists of some form of PQ disturbances. Results show that the frame identification consisting of impulsive and oscillatory transient disturbances achieved an overall accuracy rate of nearly 95%.

Original languageEnglish
Title of host publication6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
PublisherIEEE Computer Society
Pages462-465
Number of pages4
Volume2
ISBN (Print)0780367030, 9780780367036
DOIs
Publication statusPublished - 2001
Event6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Kuala Lumpur
Duration: 13 Aug 200116 Aug 2001

Other

Other6th International Symposium on Signal Processing and Its Applications, ISSPA 2001
CityKuala Lumpur
Period13/8/0116/8/01

Fingerprint

Power quality
Neural networks
Electric potential

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing

Cite this

Hussain, A., Sukairi, M. H., Mohamed, A., & Mohamed, R. (2001). Automatic detection of power quality disturbances and identification of transient signals. In 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis (Vol. 2, pp. 462-465). [950180] IEEE Computer Society. https://doi.org/10.1109/ISSPA.2001.950180

Automatic detection of power quality disturbances and identification of transient signals. / Hussain, Aini; Sukairi, M. H.; Mohamed, Azah; Mohamed, Ramizi.

6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis. Vol. 2 IEEE Computer Society, 2001. p. 462-465 950180.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hussain, A, Sukairi, MH, Mohamed, A & Mohamed, R 2001, Automatic detection of power quality disturbances and identification of transient signals. in 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis. vol. 2, 950180, IEEE Computer Society, pp. 462-465, 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001, Kuala Lumpur, 13/8/01. https://doi.org/10.1109/ISSPA.2001.950180
Hussain A, Sukairi MH, Mohamed A, Mohamed R. Automatic detection of power quality disturbances and identification of transient signals. In 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis. Vol. 2. IEEE Computer Society. 2001. p. 462-465. 950180 https://doi.org/10.1109/ISSPA.2001.950180
Hussain, Aini ; Sukairi, M. H. ; Mohamed, Azah ; Mohamed, Ramizi. / Automatic detection of power quality disturbances and identification of transient signals. 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis. Vol. 2 IEEE Computer Society, 2001. pp. 462-465
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