Intelligent Diagnostics of Insulation Degradation of High-Voltage Cable Lines in Mines Based on Deep Learning Methods

<jats:p>The paper presents the development and validation of an intelligent diagnostic method for high voltage 6 kV cable insulation operating in underground mining conditions. The proposed approach is based on deep learning techniques to detect early insulation degradation without interrupting normal equipment operation. The results demonstrate high classification accuracy and strong noise immunity under conditions typical for coal and ore mining industries. The industrial significance of the study lies in improving the reliability of underground power supply systems and reducing the risk of fires and emergency shutdowns. For mining and uranium production enterprises, the implementation of intelligent diagnostics has substantial industrial importance, as it supports a preventive industrial safety strategy and minimizes economic losses associated with equipment downtime.</jats:p>