In this article actual topics concerned with mechanical properties of bulk materials, usage of computer vision and artificial neural networks in this research are discussed. The main principles of the system for analysis of bulk materials mechanical characteristics are described. Bulk material outflow behaviour with predefined parameters (particles shapes and radius, coefficients of friction, etc.) was modelled. The outflow was modelled from the calibrated conical funnel. Obtained dependencies between mechanical characteristics and pile geometrical properties are represented as diagrams and graphs.

Nowadays pelletizing drums are widely used in the steel industry. These units are characterized by high endurance and low cost of maintenance. However, use and control of these units in the process of coarsening have a number of issues. For most of the cases pelletizing drums are “black box” and control accuracy can not be estimated exactly. It is explained by low existing theoretical basis of this production process. Particularly it is tied up with the variability of the bulk materials (charges) parameters supplied to the unit. Overcome of this issues can be reached with development of intelligent control systems for drum pelletizing machines. Main requirement for such systems is possibility to level or consider the effect of charges properties variability in control. However, it is necessary to study the behavior of bulk materials inside the units. Visual assessment of pelletization does not allow to evaluate the ongoing physical processes. Development of mathematical and numerical models can help studying the process and take a lot of parameters into account including charges properties and even interaction with water. But the adequacy of the resulting models also has to be clarified using physical devices to record or capture bulk materials behavior inside the units. This research proposes a DEM simulation test of the concept for bulk material behavior control through the recognition of the mixture movement fragments using special capsules. This part is dedicated to the simulation model set up and extracting the particles trajectories for further processing.

Destruction of rocks and artificial composites is carried out in various ways. One of the most common methods is the impact fracture. The conical pick of JCB HM380 hydraulic breaker was used as the impact tool. The experimental study of rock fracture was carried out on an artificial composite—concrete. The depth of penetration of the pick into concrete was used as the test parameter. The model was based on the model of Professor V. B. Sokolinsky. The model developed in this work takes into account the degree of bluntness of the tool insingle and multiple impact. The system was considered as a two-component system due to the high stiffness of the pick–granite contact (as against the hammer piston–pick stiffness). The wave processes in the pick were disregarded because of the small length of the pick. The pick penetration depth in rocks was calculated theoretically, using the developed mathematical model, at each impact of the pick, and then was compared with the experimental data. The fracture tests also used JCB HM380 breaker and concrete. The penetration depth was determined from the step-frame analysis of video filming of the process. It is found that the pick blunting causes a monotonic increase in the rock resistance to the pick penetration, both in single and multiple impact, while the depth of the tool penetration and the blow time decrease (as compared with the initial state of the tool, by 28% and 20%, respectively).