Analysis of Diagnostic Methods and Energy of Production Systems Drives

Author:

Kuric Ivan,Klačková IvanaORCID,Nikitin Yury RafailovichORCID,Zajačko IvanORCID,Císar MiroslavORCID,Tucki KarolORCID

Abstract

This article deals with solving the urgent scientific problem of the diagnostics of drives of technological robotized workplaces with support of sensors. The dependence of diagnostic parameters on the technical state of drives of automated technological systems, which is of great economic importance for industrial enterprises, is being investigated. Diagnostic models have been developed based on sensory systems to diagnose drive models of technological robotized workplaces. The use of these models may also include monitoring systems in which it is possible to build a system for identifying detected changes. These systems identify many contradictory changes and thereby reduce the false alarm frequency of monitoring sensory systems. Numerous methods for solving technical diagnostics problems are often based on methods based on mathematical models describing work processes, as well as on spectral analysis of measured parameters, such as vibrations, noise, and electric current. A fuzzy inference system for assessing the technical condition, a system for estimating the residual resource of drives, and asystem for calculating diagnostic intervals based on fuzzy knowledge have been developed. Based on the historical trend of the diagnostic parameters, the intelligent diagnostic system determines the current technical condition of the actuator and predicts future technical condition changes, determines the remaining service life and the time intervals for diagnostics. The analysis of the time spent on planned preventive maintenance of technological equipment makes it possible to conclude that, after the modernization of equipment in 2018, the repair time was reduced from 350 h to 260 h per year (26%). Since 2019, there is a tendency to increase repair time by 30 h each year.

Funder

Agentúra na Podporu Výskumu a Vývoja

Publisher

MDPI AG

Subject

Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering

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