Availability Assessing Intelligent Diagnostic System with Relearning after Complex Equipment Failures: Structural-Automata Model-based Methodology of Markov's Analysis

In critical systems and complex equipment, the availability of the system, the ability to measure it, and knowing how to influence it play a key role. A relearning diagnostic means of the complex system is one way to improve availability by reducing the number of latent failures. Thus, this paper is devoted to the construction and analysis of such a model of a relearning diagnostic means using a methodology based on base events and a structural-automata model. The result of the work is a created and verified model of such a system, as well as conclusions from experiments on this model on ways and recommendations for increasing the availability factor by retraining the diagnostic system.