Babokin G. I. – National Research Technological University “MISIS”, Moscow, the Russian Federation.
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Shprekher D. M. – Tula State University, Tula, the Russian Federation. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Kolesnikov E. B. – Novomoskovsk branch (institute) of D. Mendeleyev University of Chemical Technology,
Novomoskovsk, Tula region, the Russian Federation. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

The structure is described of the organization and building of equipment for technical diagnostics of complex objects by
the example of a mining electromechanical complex, which is based on a shearer-loader. Objects under control are the
electromechanical systems (EMS) containing asynchronous engines of various power; hydraulic knots, the high-voltage
and low-voltage switching equipment; electronic power converters (frequency, voltage, rectifiers); gearboxes of conveyor
and mining shearer; transformers. Process of diagnosing is carried out taking into account factors of the external
environment. The functional scheme of a diagnostic complex includes three levels of hierarchy. Each level of hierarchy
acts as managing in relation to all subordinate and as operated, subordinated, in relation to the higher one. The lower
level contains the sensors and transforming equipment measuring the parameters of EMS and factors of the external
environment, modules of input-output and isolated barriers. The average level contains technical means of interfaces
transformation and the subsequent collecting, temporary switching of telemetric messages. The top level includes set of
the automated working places of a dispatcher, functioning under the control of special software. At the root of special
software for the diagnosis of technical states are the neural network algorithms allowing to solve the problems of control
and forecasting EMS technical states. These algorithms are opened and adjusted with a possibility of adding new
diagnostic signs. The algorithms of diagnosing used in the program are based on the results of model and field
observations and are object-oriented. It is shown that the developed equipment allows operating personnel to control
technical condition of systems of any complexity on-line, including the electromechanical equipment for explosive
atmospheres.

Key words: mine electromechanical complex; diagnostic; forecast; hierarchy; technical state; neural network; software.

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