Analysis of the state of equipment

The research area focuses on the development of methods and software-analytical tools for assessing the current technical condition of power system equipment, improving operational reliability, and preventing emergency failures.

The research activities include the development of methods for processing and analyzing data obtained from monitoring systems, measurement devices, and diagnostic complexes of energy facilities. The primary focus is on identifying indicators of equipment condition changes, detecting defects at early stages of development, and evaluating the operational characteristics of power infrastructure components.

One of the key research directions is the development of intelligent diagnostic systems based on mathematical modeling, signal analysis, machine learning, and artificial intelligence methods. Such systems enable automated assessment of equipment condition, prediction of fault development, and generation of recommendations to support maintenance decision-making.

The research includes the development of algorithms for condition monitoring of electrical networks and equipment, methods for analyzing emergency processes, technologies for predicting remaining useful life, and digital models for comprehensive reliability assessment of energy facilities.

The obtained results are aimed at improving the operational reliability of power systems, reducing the risks of emergency situations, transitioning from preventive maintenance to predictive maintenance, and advancing intelligent management systems for energy infrastructure.