Development of a system of hierarchical production rules for electrical equipment diagnosing

The process of electrical equipment diagnosing at the operational stage is a multifactor process, complicated for mathematical description and modeling, since the factors affecting the operation and technical condition of equipment can be represented not only by quantitative variables, but also by linguistic variables. In order to improve the operating performance and the level of equipment fault tolerance, it is necessary to develop diagnostic methods and models using modern information technologies that take into account the main factors that affect the technical condition of the equipment. In this paper, we solve the problem of developing a system of hierarchical production rules for electrical equipment diagnosing including measuring and expert information. The novelty is that the rules are tied to developed heterogeneous cognitive models that cover all the laws of obtaining, transmitting, processing heterogeneous data and ranking rules taking into account the path length in the models between the “condition” and “conclusion” vertices, reflecting the generalized knowledge of the duty staff. This makes it possible to reduce the knowledge base capacity containing production rules, to make the search process more efficient and to take scientifically based diagnostic decisions regarding equipment health.