ARTIFICIAL INTELLIGENCE FOR DIAGNOSTIC MANAGEMENT OF MEASURING CHANNELS

This article examines the problem of managing the diagnostics of measuring channels in automated measuring systems using artificial intelligence methods. The relevance of this research is driven by increasing demands on the reliability of measuring instruments and the need to reduce the professional risks of personnel operating energy facilities. The aim of the study is to develop mathematical and software tools to enable intelligent management of the diagnostics process for measuring channels. Network models of energy flows, mathematical models for calculating network-level losses, and models for determining the power of measuring channels are used as the methodological basis. A method for identifying unreliable measuring channels is proposed, based on energy balance analysis and artificial intelligence strategies. The economic efficiency and practical feasibility of the proposed approach, which reduces the impact of the human factor and improves operational safety, are demonstrated. The results obtained can be used at enterprises operating automated energy metering and measurement systems. Keywords: automated measuring instruments, measuring channel diagnostics, control, artificial intelligence methods, mathematical models.