Artificial Intelligence-Based Diagnosis and Analysis of Partial Discharge in High-Voltage Power Cables

Authors

  • Fatima Shaikh Department of Electrical and Electronics Engineering, B.L.D.E.A’s V.P. Dr. P.G. Halakatti College of Engineering and Technology, Vijayapura – 586103, Karnataka, India (Affiliated to Visvesvaraya Technological University, Belagavi – 590018, Karnataka, India)
  • Dr. Vinoda S. Department of Electrical and Electronics Engineering, KLE Institute of Technology, Hubballi, Karnataka, India (Affiliated to Visvesvaraya Technological University, Belagavi – 590018, Karnataka, India).

DOI:

https://doi.org/10.70917/ijcisim-2026-2230

Keywords:

Partial Discharge (PD), High-Voltage (HV), Power Cables (PC), Insulation Degradation (ID), Condition

Abstract

Partial discharge (PD) is a critical indicator of insulation deterioration in high-voltage power cables, often leading to electrical failures if undetected. Traditional diagnostic techniques, though useful, are limited by their dependency on manual interpretation and sensitivity to noise. This paper presents an Artificial Intelligence (AI)-based approach for the automated diagnosis and analysis of partial discharge in high-voltage cable systems. Python-based tools (AI) are employed for data simulation, model training, and performance validation using real and synthetic PD datasets. The system demonstrates robust detection capabilities under varying AC voltage stresses, contributing to predictive maintenance, real-time

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Published

2026-06-23

How to Cite

Fatima Shaikh, & Dr. Vinoda S. (2026). Artificial Intelligence-Based Diagnosis and Analysis of Partial Discharge in High-Voltage Power Cables. International Journal of Computer Information Systems and Industrial Management Applications, 18(1s), 33–46. https://doi.org/10.70917/ijcisim-2026-2230

Issue

Vol. 18 No. 1s (2026)

Section

Original Articles