Prospects of ecological technologies development in the Russian oil industry have been developed in the paper. Reducing the negative impact on the environment is inextricably linked with the development of applied technologies. On the basis of scientific, systematic and comparative analysis we have identified major environmental issues arising from extraction, processing and use of oil and the directions of their solution. The greatest negative impact on the environment is provided by such factors as sludge formation, burning of associated gas, increased accident rate and the use of fuel oil. A number of problems in the field of environmental safety in the oil industry may be avoided by using innovations. In this work, we have assessed the prospects for reducing the negative impact on the environment through the application of modern engineering solutions in the field of ecology. In order to reduce environmental impacts and economic costs, it is primarily proposed to develop technologies in the area of safe waste management, modernization of treatment facilities and prevention of oil and oil products spills.

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 research considers conducting orthogonal experiment (OT) as one of the stages in developing a new discrete element method (DEM) parameters calibration approach. The measured responses in experiment are the parameters obtained by DEM animation processing using machine vision system (MVS). The variable factors in experiment are DEM parameters. A brief overview of an existing calibration approaches given in the article. The choice of OT as a design of experiment tool among other mathematical tools discussed. Experiments conducted using specially developed rig where bulk material's flow captured as DEM animation. DEM animation converted to video and then processed using MVS that allow register the values of such parameters as angle of repose or expiration time (measured responses). The results of the OT show that it is possible to identify four measured responses with the most valuable correlation coefficient. DEM parameters with the biggest influence on the measured responses identified for each of the obtained regression. Obtained results are useful in learning or iterative algorithms development for DEM parameters calibration.