A Review of Modern Technologies for Automated Diagnosis of Power Transformers
Dilafruz AbdullabekovaTashkent University of Information Technologies named after Muhammad al-KhwarizmiMamatkarim SapayevTashkent University of Information Technologies named after Muhammad al-KhwarizmiMaftuna Zinaddin qizi NazerbaevaTashkent University of Information Technologies named after Muhammad al-Khwarizmi
2025en
ABI
Annotatsiya
This paper reviews modern technologies for automated diagnosis and condition monitoring of power transformers. The study considers online monitoring systems, automated dissolved gas analysis (DGA), partial discharge monitoring, ontology-based diagnostic models, and IoT/SCADA/cloud integration. The reviewed technologies enable real-time assessment of transformer condition, early fault detection, predictive maintenance, and improved operational reliability. The paper also discusses current implementation challenges, including cybersecurity, high initial costs, specialist training, and large-scale data processing.
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