Analysis of technical and technological conditions for the emergence of emergency situations during the operation of electromechanical equipment of enterprises of the mineral and raw materials complex shows that when developing the basis for ensuring safe operation, it is necessary to take into account not only the technical condition, but also the non-stationary operation of the operating conditions of equipment, and the nonstationarity of operational operating parameters of technological processes.
Violations of the operation of individual parts of the machine, not detected in time, can lead to severe accidents at work, as well as to unplanned downtime and loss of profits. That is why, the issues of obtaining and processing Big data obtained during the life cycle of electromechanical equipment, for assessing the current state of the electromechanical equipment used, timely diagnostics of emergency and pre-emergency modes of its operation, estimating the residual resource, as well as prediction the technical state on the basis of machine learning are very important.
This article is dedicated to developing the special method of data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment. This method can be used in working with big data and can allow extracting the knowledge from different data types: the plants' historical data and the factory historical data. The data of the plants contains the information about electromechanical equipment operation and the data of the factory contains the information about a production of electromechanical equipment.

The experimental studies results of the mechanical and thermo-mechanical treatment influence of wear resistance of excavator bucket tooth materials and rotary cutting tool are presented in this article. Experiments on abrasion in different rocks were investigated. In the example of 110G13L steel (Hadfield steel), it was shown that mechanical strengthening (cold hardening) is an effective way to improve wear resistance of machine parts working in abrasive environments. It was revealed that if the hardness of abrasive materials is lower than the hardness of cold hardening steel, wear resistance may increase by 10 times and if the hardness of abrasive materials is higher than the hardness of steel with cold hardening, it does not influence wear resistance. It was found that the high-temperature thermo-mechanical treatment of 30KhGSA steel increases its hardness (by 23%) and wear resistance (by 38%) by comparing with the same steel after hardening. It was concluded that the advisable use one of these methods depends on rock hardness.

The article considers the most modern and most informative methods for diagnosing faults in squirrel-cage induction motors with a short-circuited rotor. The methods are based on the evaluation of vibrations and electrical parameters, as well as coordinates during operation and are normalized when powered from a sinusoidal voltage with frequency of 50 Hz. The main advantages and disadvantages of these methods, as well as the main indicators characterizing the general technical condition of the electric motor, are described. The application of these methods when powered from a non-sinusoidal voltage is impossible due to the complex harmonic composition of current and voltage. The consequence of this composition are the ripple moment and additional power loss. The interaction of the harmonics of the inverter and subharmonics, caused by faults, leads to the occurrence of a resonance phenomenon, and therefore to a decrease in the stability of the electric drive.