open access publication

Article, Early Access, 2024

Enhanced complex wire fault diagnosis via integration of time domain reflectometry and particle swarm optimization with least square support vector machine

IET SCIENCE MEASUREMENT & TECHNOLOGY, ISSN 1751-8822, 1751-8822, 10.1049/smt2.12187

Contributors

Laib, Abderrzak [1] Chelabi, Mohamed [2] Terriche, Yacine [3] Melit, Mohammed [2] Boudjefdjouf, Hamza [4] Ahmed, Hafiz (Corresponding author) [5] Chedjara, Zakaria [6]

Affiliations

  1. [1] Univ Msila, Dept Elect Engn, Fac Technol, Msila, Algeria
    2. [NORA names: Algeria; Africa];
  2. [2] Jijel Univ, Dept Elect Engn, Jijel, Algeria
    3. [NORA names: Algeria; Africa];
  3. [3] Orsted Wind Power A S, Fredericia, Denmark
    4. [NORA names: Ørsted; Private Research; Denmark; Europe, EU; Nordic; OECD];
  4. [4] Univ Freres Mentouri Constantine, Dept Elect Engn, Constantine, Algeria
    5. [NORA names: Algeria; Africa];
  5. [5] Univ Sheffield, Nucl AMRC Midlands, Infin Pk Wy, Derby DE73 5SS, England
    6. [NORA names: United Kingdom; Europe, Non-EU; OECD];

Abstract

Overview of the particle swarm optimization (PSO) method-based tuning approach for the least square support vector machine (LSSVM) model developed in this work to diagnose faults in complex wire networks. image

Keywords

fault diagnosis, time-domain reflectometry

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