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.

This article is devoted to expanding the possibilities of assessing the technical state of the current consumption of asynchronous electric drives, as well as increasing the information capacity of diagnostic methods, in conditions of limited access to equipment and incompleteness of information. The method of spectral analysis of the electric drive current can be supplemented by an analysis of the components of the current of the Park's vector. The research of the hodograph evolution in the moment of appearance and development of defects was carried out using the example of current asymmetry in the phases of an induction motor. The result of the study is the new diagnostic parameters of the asynchronous electric drive. During the research, it was proved that the proposed diagnostic parameters allow determining the type and level of the defect. At the same time, there is no need to stop the equipment and taky it out of service for repair. Modern digital control and monitoring systems can use the proposed parameters based on the stator current of an electrical machine to improve the accuracy and reliability of obtaining diagnostic patterns and predicting their changes in order to improve the equipment maintenance systems. This approach can also be used in systems and objects where there are significant parasitic vibrations and unsteady loads. The extraction of useful information can be carried out in electric drive systems in the structure of which there is a power electric converter.

Digital technology is being introduced into all areas of human activity. However, there are a number of challenges in implementing these technologies. These include the delayed return on investment, the lack of visibility for decision-makers and, most importantly, the lack of human capacity to develop and implement digital technologies. Therefore, creating a digital training simulator for the industry is an actual task. This paper focuses on the first step in creating a digital training simulator for the industry: developing a dynamic process model. The process chosen is flotation, as it is one of the most common mineral processing methods. The simulation was performed in AVEVA Dynamic Simulation software. The model is based on a determination of reaction rate constants, for which, experiments were conducted on a laboratory pneumomechanical flotation machine with a bottom drive. The resulting model was scaled up to industrial size and its dynamic properties were investigated. In addition, the basic scheme of a computer simulator was considered, and the testing of the communication channels of a dynamic model with systems, equipment and software for digitalizing was conducted. The developed model showed acceptable results for its intended purpose, namely, an exact match to the technological process in terms of time. This helps to account for inertia and a fast response on all tested communication channels, as well as being acceptable for the real-time simulation speed of the solver.