Fault Detection in Transmission Lines: a Denial Constraint Approach

  • Nicolas Tamalu Universidade Federal do Paraná
  • Leandro Augusto Ensina Universidade Federal do Paraná / Universidade Tecnológica Federal do Paraná
  • Eduardo Cunha de Almeida Universidade Federal do Paraná https://orcid.org/0000-0002-6644-956X
  • Eduardo Henrique Monteiro Pena Universidade Tecnológica Federal do Paraná
  • Luiz Eduardo Soares de Oliveira Universidade Federal do Paraná


This paper introduces an approach for discovering denial constraints (DCs) to identify faults in transmission lines. However, the considerable volume of data in the studied scenario makes traditional DC discovery impractical due to lengthy execution times. We propose an alternative DC discovery approach that uses streaming windows to address this issue. Our experiments demonstrate that the DCs identified in pre-fault windows differ significantly from those in post-fault windows. This valuable insight enables us to detect faults autonomously, eliminating the need for human intervention (i.e., an unsupervised method). The experimental evaluation featuring diverse fault events reveals that our approach achieves fault detection with remarkable 100% accuracy.
Palavras-chave: denial constraints, fault analysis, power transmission


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TAMALU, Nicolas; ENSINA, Leandro Augusto; CUNHA DE ALMEIDA, Eduardo; PENA, Eduardo Henrique Monteiro; OLIVEIRA, Luiz Eduardo Soares de. Fault Detection in Transmission Lines: a Denial Constraint Approach. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 38. , 2023, Belo Horizonte/MG. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 231-243. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2023.231718.