Creation of Predictive Analytics System for Power Energy Objects

Paper presents a review of diagnostic methods and forecasting the technical condition. The relevance of the task of forecasting the values of technological parameters in the framework of solving the problem of forecasting the technical condition of power equipment for the condition-based repairs organization is shown. The architecture of the predictive analytics system for energy facilities has been developed. Methods of pre-processing Big data and forecasting parameter values are considered. The effectiveness of artificial neural networks in solving these problems is shown.