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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

DEVELOPMENT OF AN AI-BASED FRAMEWORK FOR REAL-TIME FAULT ANALYSIS AND CLASSIFICATION IN ELECTRICAL TRANSMISSION NETWORKS

Srikakolapu Madhu

Adabala Siva Sarapakara Rao

Bonam Venkata Chalamayya Engineering College Odalarevu AP
DOI:https://doi.org/10.55041/ijcope.v2i4.595

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

The reliability of transmission lines is crucial for the efficient operation of power systems, as they are prone to faults such as line-to-ground (L–G), line-to-line (L–L), double line-to-ground (L–L–G), and three-phase faults. These faults may arise due to environmental conditions, insulation breakdown, or equipment failures, leading to system instability, equipment damage, and power outages if not detected promptly. Traditional protection methods, such as distance relays and overcurrent protection, rely on fixed thresholds and often lack adaptability under dynamic conditions. To address these limitations, this study proposes an AI-based real-time fault detection and classification system using deep learning. A transmission line model is developed in MATLAB/Simulink to generate fault data. Extracted features using Fast Fourier Transform (FFT) are fed into a hybrid CNN-LSTM model. The proposed system achieves approximately 98% accuracy with millisecond-level detection time, ensuring reliable and efficient power system protection.

Keywords: Artificial Intelligence (AI); Deep Learning; Fault Detection; Fault Classification; Transmission Lines; Real-Time Monitoring; Smart Grid.

How to Cite this Paper

Madhu, S. (2026). Development of an AI-Based Framework for Real-Time Fault Analysis and Classification in Electrical Transmission Networks. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.595

Madhu, Srikakolapu. "Development of an AI-Based Framework for Real-Time Fault Analysis and Classification in Electrical Transmission Networks." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.595.

Madhu, Srikakolapu. "Development of an AI-Based Framework for Real-Time Fault Analysis and Classification in Electrical Transmission Networks." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.595.

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References


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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Apr 22 2026
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