The method of automated diagnostics and control of the technical condition of the electric drive of mining machines, which consists in monitoring the current with subsequent spectral analysis of the received signal, is considered. It allows using the ATmega16 microcontroller to determine with sufficient accuracy the current technical state of the electric drive elements. The aim of the work is to prove the possibility and justify the effectiveness of the use of microprocessor technology in the mining industry to automate the diagnosis of machinery units. The adequacy of the developed methodology for determining the identification frequencies is confirmed by experimental data in the low-frequency region of the spectrum. The conclusion of this article is that a comparative analysis of the calculated and experimentally obtained amplitude-frequency characteristics of individual components of the drive motor and elements of the transmission of the executing body of the KP21 tunnelling machine has confirmed their adequacy.

Keywords: electric drive of a tunneling machine, automated diagnostics and control, current monitoring, spectral analysis, increased reliability of tunneling equipment

The article considers one of the ways to improve the reliability of mining equipment, by eliminating sudden failures and reducing the severity of their consequences, based on the use of digital technologies and automated control systems for its technical condition and online diagnostics. It is proposed to use the methods of diagnostics and automated control of the technical condition of power electrical machines, which consist in monitoring the current with subsequent spectral analysis of the recorded signal. The method allows to determine the current technical condition of the engine elements with sufficient accuracy. A high-performance RISC microcontroller of the AVR ATmega16 family was adopted as the constituent elements of the diagnostic complex, which contains a fast Harvard processor, program memory, data memory, input / output ports and various interface circuits.

Keywords: reliability of mining equipment, diagnostics, automated control, current monitoring, spectral analysis

The article presents the results of checking the adequacy of the method of online diagnostics and automated control of the technical condition of the electromechanical drive of the KP21 mining machine with an asynchronous squirrel-cage motor, proposed earlier by the authors. The method of experimental production studies provides for the connection of the measuring complex to the stator winding of one of the phases of the electric motor. The measurements were carried out under various operating conditions of the combine, corresponding to various technical conditions of the facility. A comparative analysis of the technical condition of the diagnosed nodes and the values ​​of the normalized amplitudes of the corresponding frequencies led to the conclusion: the defect must be fixed if the signal amplitude exceeds the value of 10% of the maximum, and the defect is significant and needs to be eliminated if the amplitude value exceeds 30%. To use the obtained research results in practice, an integral nomogram of the correspondence between the operating time of the combine harvester and the amplitude - frequency characteristic of the stator current of the drive motor of the cutting body is proposed. The results obtained are taken as a basis for correcting the schedule of preventive maintenance and maintenance of the cutting body of mining machines KP21 when operating in the appropriate mining and geological conditions.

Keywords: reliability of mining equipment, online diagnostics, automated control, current monitoring, maintenance and repair

Details are given as for the results of production researches of reliability of Tunnelling Combines KP21, produced by JSC Kopeisk Engineering Plant, in conditions of Almaznaya Mine of Coal Company "Gukovugol" when driving preparatory developments with section up to 16 sq.m and strength of country rock up to 7 units according to Protodyakonov Rock Strength Scale. The obtained data allowed to define average operating time before breakage, as well as to make the list of details and knots having the greatest effect on reliability of the combine. The results processed allowed to calculate numerical characteristics of empirical distribution, which are similar to numerical characteristics of a random variable: ensemble average, dispersion, average quadratic deviation, variation coefficient, etc.

Keywords: tunnelling combine of selective action, reliability, operating time before breakage