Open AccessFault classification and faulted phase selection for transmission line using morphological edge detection filter
Author(s) -
Salehi Moslem,
Namdari Farhad
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0999
Subject(s) - polarity (international relations) , filter (signal processing) , fault (geology) , transient (computer programming) , computer science , electric power transmission , transmission line , matlab , line (geometry) , enhanced data rates for gsm evolution , mathematical morphology , signal (programming language) , phase (matter) , algorithm , morphological gradient , selection (genetic algorithm) , pattern recognition (psychology) , edge detection , artificial intelligence , engineering , mathematics , physics , computer vision , telecommunications , geology , electrical engineering , seismology , image processing , geometry , quantum mechanics , image (mathematics) , cell , genetics , biology , operating system , programming language
In this study, a novel algorithm for detecting and classifying faults in transmission lines is proposed. The algorithm is based on mathematical morphology and initial current travelling waves. A new morphological edge detection (MED) filter to extract the transient features from the original fault signal is designed. This MED filter can fast and accurately detect the arrival time and polarity of travelling waves in all conditions. The appropriate criteria of fault classification and faulted‐phase selection are introduced based on polarity of initial current travelling waves. The simulations based on the electromagnetic transients program and MATLAB have been done to evaluate the validity of the proposed algorithm.