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This research focuses on utilizing machine learning to identify and classify defects in electrical power transmission lines. The suggested technique takes as inputs the voltages of one end and the three-phase currents. For the examination of each of the three process stages, the support vector machine method with hyper-parameter tuning has been used for fault identification and classification. An application that can forecast more than 98% of the time uses the trained model. The simulation results showed that the current support vector machine-based technology is effective in identifying and categorizing transmission line issues. The method's adaptability is tested by simulating various defects with varying settings. It is possible to expand the suggested approach to include the Power System's distribution network. Signal analysis and numerous simulations are carried out inside the MATLAB environment.

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An Artificial Intelligence Approach for Prediction and Classification of Transmission Line Faults

  • 会议论文

  • 发表日期：

    2025年

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  • Kalyan Gajare,
  • Shahid A. Iqbal,
  • Jagdish More,
  • Jayesh Kolhe,
  • Ilyas Dhobi,
  • Rushikesh Patil

摘要

This research focuses on utilizing machine learning to identify and classify defects in electrical power transmission lines. The suggested technique takes as inputs the voltages of one end and the three-phase currents. For the examination of each of the three process stages, the support vector machine method with hyper-parameter tuning has been used for fault identification and classification. An application that can forecast more than 98% of the time uses the trained model. The simulation results showed that the current support vector machine-based technology is effective in identifying and categorizing transmission line issues. The method's adaptability is tested by simulating various defects with varying settings. It is possible to expand the suggested approach to include the Power System's distribution network. Signal analysis and numerous simulations are carried out inside the MATLAB environment.