Authors: E.G. Kuzin

Title of the article: Predictive control of the technical condition of mining transport machines

Year: 2023, Issue: 1, Pages: 41-49

Branch of knowledge: 2.8.8. Geotechnology, Mining machines (engineering)

Index UDK: 622.647, 622.271

DOI: 10.26730/1816-4528-2023-1-41-49

Abstract: The paper considers issues of predictive control of the technical condition of mining transport machines in relation to the flow transport systems of mining enterprises. The relevance of transport machine components service life management is shown. The introduction of advanced technologies to ensure the strategy of sustainable development of the mining industry of the Russian Federation is being taken into account. The term ‘management’ is understood not just as "increasing" the service life, but also as its compliance with the "set targets", including the concepts of energy-efficient operation. An effective solution to the issues of predictive control of the state of machines is based on the choice of: a class of components to be evaluated, methods of evaluation and forecasting, and the development of an adequate management model. It is shown, that for diagnostic purposes it is sufficient to evaluate such a class of components as bearings, gears, windings of electric machines, machines and housings, shafts, couplings, drum shells, etc. Available and effective methods of technical diagnostics are given, most of them relate to non-destructive testing methods, but require adaptation to the conditions of mining and processing enterprises. The main methods include visual control, acoustic control, vibration diagnostics, thermal control methods and control of the condition of lubricants (oils and greases). A feature of the technical condition management tasks is the choice of adequate methods for predicting its changes with minimizing the influence of the qualifications of maintenance and repair personnel. The classification of forecasting methods in relation to flow transport systems is given. The theory of the development of complex technical systems is taken into account. The rationale for the transition to intelligent expert systems is given. It does not require the constant participation of specialists (experts). Neural networks also process the extensive base of accumulated operational experience. It is important to understand that an intelligent expert system is designed not to replace a person (except in emergencies), but to support decision-making. It helps to operate efficiently the flow-through transport systems at a hazardous production facility (mine, mine, processing plant).

Key words: predictive control mining transport machines technical diagnostics forecasting methods vibration diagnostics thermal control technical condition assessment intelligent expert systems

Receiving date: 19.09.2022

Approval date: 06.10.2022

Publication date: 09.03.2023

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