Scholarlink

Amidst the ongoing rapid growth in the power grid, faults in distribution lines must be detected urgently. Discrete Wavelet Transform (DWT) is used here for detecting short-circuit faults using Matlab and Simulink, demonstrating a single-ended technique where current signals of each end were measured using DWT. Peak detail coefficients were compared with threshold coefficients to identify the type of faults. A hardware prototype was designed and implemented using a Raspberry Pi connected to voltage and current sensors through Arduino. The Sensors’ readings were used for creating an IoT-based monitoring system where DWT was applied on the current waveform. This verified the inexpensive DWT-based fault detection method for detecting short-circuit faults in distribution lines. This project contributes to smart grid technology by integrating digital components within distribution lines.

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Implementation of an Inexpensive IOT-Based Distribution Line Fault Detection Using Raspberry Pi

  • 会议论文

  • 发表日期：

    2026年

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  • Raafiu Ashiquzzaman Mahmood,
  • Taremun Arefin,
  • Md. Roman Khan,
  • Salma Islam Mim,
  • Shahriar Khan

摘要

Amidst the ongoing rapid growth in the power grid, faults in distribution lines must be detected urgently. Discrete Wavelet Transform (DWT) is used here for detecting short-circuit faults using Matlab and Simulink, demonstrating a single-ended technique where current signals of each end were measured using DWT. Peak detail coefficients were compared with threshold coefficients to identify the type of faults. A hardware prototype was designed and implemented using a Raspberry Pi connected to voltage and current sensors through Arduino. The Sensors’ readings were used for creating an IoT-based monitoring system where DWT was applied on the current waveform. This verified the inexpensive DWT-based fault detection method for detecting short-circuit faults in distribution lines. This project contributes to smart grid technology by integrating digital components within distribution lines.