Abstract
BACKGROUND: The economic component of the effective functioning of technological machines consists in their uninterrupted operation when performing various tasks in such industries as construction, road, agriculture, etc. It is currently possible to take into account the variety of operating conditions of technological machines and constantly changing loading modes by using digital technologies that allow creating an array of databases not only in real time, but also for an individual machine. An urgent task is to create methods for collecting information about the operating modes of the machine, the factors causing changes in the efficiency of operation, the development of algorithms for making decisions about maintaining the working condition of all units and systems of the machine, preventing their failures and non-production downtime of the machine as a whole. AIMS: to ensure the effective functioning of a single technological machine by managing the risks of failures, by adjusting the frequency of maintenance and periods of repair and restoration effects based on real-time data on the technical condition and digital processing of decision-making information. MATERIALS AND METHODS: the nature of changes in the technical condition of aggregates and systems of technological machines in the theory of systems is most often considered as random due to the high probability of uncertainty of factorial influence. It is proposed to consider the problem of failure risk management of system elements and aggregates of technological machines using the basic provisions of the theory of emissions of random processes. The object of the study is a diesel engine of a technological machine with an example of monitoring the technical condition of the fuel system. RESULTS: The substantiation of the expediency of performing maintenance and repair and restoration effects of technological machines according to need is presented. The adjustment of the maintenance frequency was carried out based on the results of these changes in the performance of the machine, in particular the internal combustion engine fuel system. To develop an algorithm for the formation of a data array, typical architectures for collecting and processing information using digital platforms for decision-making on the intensity of parameter changes are used, as an example, oscillograms of pressure changes during the operation of the internal combustion engine power system are presented. CONCLUSIONS: A module for diagnosing the technical condition and efficiency of the internal combustion engine of a single technological machine in real time has been developed. It is proposed to introduce an intelligent decision-making system with subsequent transformation into the image of a digital double of failure risk management and control of the efficiency of the machine for various operating conditions.
Published Version
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