This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

The article presents a study of implementations of information technologies for energy saving. The study provides an analysis of cloud platforms used in the energy sector. Most platforms are used to increase equipment load factors, diagnose it, or integrate the energy infrastructure of individual systems into large systems. The article discusses the role of man in the process of improving energy efficiency. As a result of the research, it is found that the user's connection to energy saving will act as a significant motivation. The proposed cloud platform focused on the personalization of energy actions will create the prerequisites for the formation of a smart consumer. The article describes the structure and functionality of the system. As a result of the platform implementation, the user will be able not only to reduce his bills for energy, but to see the real effect of his actions in the overall balance.

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.

Electromechanical equipment is widely used. It is used in industrial enterprises, in the spheres of public services, in everyday life, etc. Maintenance servicing of electromechanical equipment is an important part of its life cycle. High-quality and timely service can extend the life of the electromechanical equipment. The creation of special systems that simplify the process of servicing electromechanical equipment is an urgent task. Such systems can shorten the time for maintenance of electrical equipment, and, therefore, reduce the cost of maintenance in general. This article presents an analysis of information on the operation of service services for maintenance and repair of electromechanical equipment, identifies the list of services, and estimates the time required to perform basic service operations. The structure of the augmented reality system is presented, the ways of interaction of the augmented reality system with the automated control systems working at the enterprise are presented.

The frequency of maintenance of electromechanical equipment depends on the plant, which uses and runs this equipment. Very often the maintenance frequency is poorly correlated with the actual state of the electromechanical equipment. Furthermore, traditional methods of diagnosis sometimes cannot work without stopping the process (for example, for equipment located in hard to reach places) and so the maintenance costs are increased. This problem can be solved using the indirect methods of diagnosing of the electromechanical equipment. The indirect methods often use the parameters in the real time and seldom use the parameters of traditional diagnostic methods for determination of the resource of electromechanical equipment. This article is dedicated to developing the structure of a special automated control system. This system must use the big flow of the information about the direct and indirect parameters of the equipment state from plants from different areas of industry and factories which produce the electromechanical equipment.

The system of the preventive maintenance (PM), accepted at production association LLC KINEF, taking into account safe operation and health assessment, is analyzed. Statistical data of results of diagnostics are processed; options of the increase of the integrated reliability indicator of the system of pipeline transport are offered. The trend lines of a condition change of the pipeline in time and the approximate curves of diagnostic data of nondestructive inspection technique with creation of the long-term forecast of its technical condition was constructed. The option of correction of the accepted PM system with the analysis of quantitative change of an indicator of reliability was developed, by which application of the percentage of uptime will increase from 0.909 to 0.957.

The article discusses the extraction of solid mineral resources (SMR) from the bottom, such as ferromanganese nodules (FMN) and cobalt-manganese crusts (CMC), occurring in both offshore and deep regions of the World Ocean. For separating and lifting the water surface is used mining complex, which includes a hydraulically dragheads and intermediate capsule with atmospheric pressure introduced into the of extraction process in order to increase energy efficiency through the organization of a two-stage hydroascent, the first stage is carried out by external hydrostatic pressure. To determine the optimum depth of immersion of the intermediate capsule composed mathematical model. It is based on the sustainable hydroascent provided at the first stage transport (from the bottom to capsule), and reducing power consumption slurry pump performing the second stage transport (from the capsule to the sea surface). In determining the rational immersion depth were taken into account design features of slurry pipeline, mine geological parameters, the parameters of extracted minerals, performance of dragheads, the slurry flow parameters, such as concentration, consistency, density. Presents an example calculation and determined the optimal capsule insertion depth for offshore geological environments.

The article deals with the principle of evaluation of technical condition, based on a comprehensive analysis of the motor parameters which is a main unit in mechanical engineering. Diagnostics system and residential life assessment of electromechanical equipment is presented based on the AC engine and algorithms of its work. The important challenge of diagnostics remains the well-timed faults detection and maintenance and repair organization. The solution of such challenge remains accuracy and reliability of diagnostic systems.

This paper analyzes the possibility of using electric vehicles as a controlled distributed generator. Aggregation of demand and supply for electric power with the participation of batteries allows us to solve the problem of the development of the electric grid infrastructure of megacities. The absence in some areas of the city of opportunities for technological connection of consumers and significant deterioration of the network infrastructure is solved by the integration of electric vehicles in the city's power system. The article shows that information technology allows you to control the energy curve over time. At the same time, the power schedule in the loaded power centers will be deprived of pronounced highs and lows, which favorably affects the loading of generating capacities. Informatization of electric transport and the use of a digital platform will eventually become part of the concept of "smart city".

The article discusses the structure of autonomous electrical systems with an electric drive and an electric energy generation system. An approach is described for assessing the overall efficiency of technological cycle equipment with specification of parameters that must be considered when calculating it. The necessity of taking into account energy efficiency and operability indicators of autonomous electric complexes is substantiated. The effectiveness of the use of autonomous systems decreases throughout the entire life cycle due to wear and tear. As the operability of electromechanical equipment, an indicator of the residual resource is selected. The calculation of the residual resource, with the definition of its boundary values and recommendations for further use. Nominal energy efficiency parameters of autonomous electrotechnical complexes with electric drive deteriorate during operation, which also needs to be taken into account. To simplify the assessment of the operational state of electromechanical equipment, a state diagram is presented that allows you to track the dynamics of degradation of individual nodes. Taking into account the described indicators and means of control, it is possible to increase the efficiency of using autonomous complexes.

The oil&gas enterprises have their own safety concerns list. Poor maintenance of equipment is one of the top safety concerns for many enterprises. There are a lot of methods of increasing of safety, but its shouldn’t be used alone. A complex approach and addition the modern technologies in safety ensuring make possible not only increase the quality but increase the efficiently of production. There are a lot of kinds of quality improving of maintenance of electromechanical equipment, one of them are the augmented reality system. This is a new technology and there are no methods and effective estimation for developing and using this technology in industrial production. Developing the special unified modules of augmented reality for maintenance of electromechanical equipment is the actual task. The aim of this research-to identify possible uses, to estimate the effectiveness in ensuring the safety of production and to develop a way of integrating into typical process control systems of the augmented reality system for maintenance of electromechanical equipment.

The article describes the current situation in the global uranium concentrate market, explains the reasons for the formation of an excess amount of finished goods and the subsequent decreasein prices. The authorsevaluated the prospects of using market mechanisms to improve the financial results of Russian uranium mining enterprises. The location of the main mining centers in comparison with the centers of consumption of finished goods, pricing for the products of uranium mining companies, the dynamics of price changes over the past 20 years, the influence of non-market factors on the supply of finished products are analyzed.This study led to the conclusion that the expectation of changes in the market situation is not viable in a long term. The authors outlined the direction to improve the profitability of mining enterprises by introducing technological changes aimed at reducing the cost of the final product.