Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning

Pallav Kumar Bera, Rajesh Kumar, Can Isik

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

Abstract

This paper proposes methods to identify 40 different types of internal faults in an Indirect Symmetrical Phase Shift Transformer (ISPST). The ISPST was modeled using Power System Computer Aided Design (PSCAD)/ Electromagnetic Transients including DC (EMTDC). The internal faults were simulated by varying the transformer tapping, backward and forward phase shifts, loading, and percentage of winding faulted. Data for 960 cases of each type of fault was recorded. A series of features were extracted for a, b, and c phases from time, frequency, time-frequency, and information theory domains. The importance of the extracted features was evaluated through univariate tests which helped to reduce the number of features. The selected features were then used for training five state-of-the-art machine learning classifiers. Extremely Random Trees and Random Forest, the ensemble-based learners, achieved the accuracy of 98.76% and 97.54% respectively outperforming Multilayer Perceptron (96.13%), Logistic Regression (93.54%), and Support Vector Machines (92.60%).

Original languageEnglish (US)
Title of host publication2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538675687
DOIs
StatePublished - Feb 14 2019
Event2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018 - Louisville, United States
Duration: Dec 6 2018Dec 8 2018

Publication series

Name2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018
Volume2019-January

Conference

Conference2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018
CountryUnited States
CityLouisville
Period12/6/1812/8/18

Fingerprint

Phase shift
Information theory
Multilayer neural networks
Support vector machines
Learning systems
Logistics
Computer aided design
Classifiers

Keywords

  • Ensemble Learning
  • Fault Identification
  • Phase Shift Transformer

ASJC Scopus subject areas

  • Signal Processing
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

Bera, P. K., Kumar, R., & Isik, C. (2019). Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning. In 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018 [8705100] (2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018; Vol. 2019-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2018.8705100

Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning. / Bera, Pallav Kumar; Kumar, Rajesh; Isik, Can.

2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018. Institute of Electrical and Electronics Engineers Inc., 2019. 8705100 (2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018; Vol. 2019-January).

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

Bera, PK, Kumar, R & Isik, C 2019, Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning. in 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018., 8705100, 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, vol. 2019-January, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, Louisville, United States, 12/6/18. https://doi.org/10.1109/ISSPIT.2018.8705100
Bera PK, Kumar R, Isik C. Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning. In 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018. Institute of Electrical and Electronics Engineers Inc. 2019. 8705100. (2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018). https://doi.org/10.1109/ISSPIT.2018.8705100
Bera, Pallav Kumar ; Kumar, Rajesh ; Isik, Can. / Identification of internal faults in indirect symmetrical phase shift transformers using ensemble learning. 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018. Institute of Electrical and Electronics Engineers Inc., 2019. (2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018).
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