A lot of researchers are developing new DEM parameters calibration approaches based on an experiment plan or the use of learning algorithms. This research is aimed at improving iterative algorithms frequently used for calibration. The big time consumption as a main problem of iterative algorithms is questioned. It is proposed to use Random forest algorithm to determine DEM parameters impact on the measured bulk responses. Measured responses are the parameters obtained by image processing using a technical vision system. As a result of 200 experiments processing, DEM parameters impact values on each bulk response were generated and presented as histograms. Obtained results were interpreted on the basis of the bulk material behavior and its physical properties. There is a discussion on the possibility of developing a universal DEM parameters calibration method based on the iterative algorithm.

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 problem of DEM models calibration is considered in the article. It is proposed to divide models input parameters into those that require iterative calibration and those that are recommended to measure directly. A new method for model calibration based on the design of the experiment for iteratively calibrated parameters is proposed. The experiment is conducted using a specially designed stand. The results are processed with technical vision algorithms. Approximating functions are obtained and the error of the implemented software and hardware complex is estimated. The prospects of the obtained results are discussed.