Method for Assessing the Instability of Technological Parameters of Nuclear Power Plant Unit Electrical Equipment Using Information and Control Systems
A method has been proposed to determine the level of chaotic changes in technological characteristics, enabling more accurate failure prediction. Key indicators such as fractal dimension, fractal time, and fractal time dimension have been identified, allowing for quantitative assessment of techno-logical process instability levels. The application of fractal analysis in monitoring technological parameters helps uncover hidden patterns in equipment behavior that remain inaccessible with traditional analysis methods. This differentiation between normal parameter fluctuations and potentially hazardous deviations significantly enhances diagnostic accuracy. It has been found that the fractal dimension of a signal can serve as an indicator of the stability of a technological process. The research results are explained by the ability of fractal analysis methods to reflect the nonlinear structure of processes and detect deviations in parameter dynamics. This enables effective prediction of technological system behavior even under complex operating conditions. Practical application of the obtained results is feasible within nuclear power plant information and control systems, particularly in automated monitoring and predictive diagnostics systems for equipment. Implementing fractal analysis will improve equipment condition assessment efficiency, optimize maintenance processes, and enhance the overall reliability and safety of power units.
