This paper carries out the research on the continental mining of solid minerals and on the search of the alternative solutions of raw material’s procurement for leading industries. A value of conducting underwater operations for extraction of shelf zone’s ferromanganese nodules is specified. Schematic diagram of conducting mining operations is submitted. The construction of a mining complex for mining ferromanganese nodules of the Baltic Sea with the possibility of its separation partial enrichment on the seabed during the process of production is proposed. An analytical model of the system with bottom device and flexible traction element is given. The interaction between a flexible traction element and a bottom-mining unit allows to define the character of relative motion and also to describe the position of the flexible traction element as it moves in the aquatic environment. Specific conditions for steady operation of the complex for its inseparable moving on a seabed are presented.

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.

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.