The maintenance of oil pumps is a complex task for any operating organization, and for an industrial enterprise in the oil and gas sector of the economy, this issue has a high degree of urgency. One of the reasons for this is a wide spread of pumping equipment in all areas of oil and gas enterprises. At the same time, an aggressive environment, uneven load, remote facilities, and harsh climatic zones (especially in the areas of the Arctic region or production platforms) are factors that make it relevant to develop special systems that help or simplify the maintenance of pumping equipment. Dynamic modeling is one of the modern technologies which allows for solving the urgent issue of assessing the technical condition of equipment. It is the basis of systems that carry out diagnostics and prognostic calculations and allow for assessing the dynamic state of objects under various conditions of their operation, among other functions. Augmented reality technology is a technology that allows for reducing the time for equipment maintenance by reducing the time for searching and processing various information required in the maintenance process. This paper presents an investigation of the effectiveness of an augmented reality and a dynamic simulation system collaboration in oil pump maintenance. Since there is insufficient research on the joint application of these two technologies, the urgent issue is to prove the effectiveness of such collaboration. For this purpose, this paper provides a description of the system structure, gives a description of the development process of the augmented reality system application and tests the application using Microsoft HoloLens 2.

The efficiency issue of energy systems in the oil and gas industry is a crucial factor nowadays. Energy share in the production costs of oil and gas can reach 50%. Among the most important energy equipment are the electric drives of the pumps, compressors, auxiliary units, etc. The paper considered the lifecycle of the electric drives used at oil and gas fields and evaluated their efficiency parameters during periods of operational wear or malfunctioning. At the same time, the lifecycle of the energy equipment was seen as its technical state during operation. Based on the spectral analysis of the current using the finite Fourier transform (FFT), the main frequency components were identified that characterize the type and level of malfunction, taking into account defined efficiency indicators of the electric drive. A technique for assessing the technical state of an electric drive was proposed based on the normalized levels of the amplitudes of the frequency components. Predictive management of the electric drive was implemented in terms of correcting the control system when a malfunction occurs, providing the required efficiency indicators. Boundaries for the technical state of the electric drive were determined. Recommendations for further operation, terms of maintenance and repair or preventive management were presented.

The presented research is focused on two issues. The first one is finding additional parameters that characterize the technical condition of an electric machine according to the current consumption. The second one is increasing of the informativeness of diagnostic methods in conditions of limited access to equipment and incomplete information. The paper discusses a method for diagnosing low and medium power asynchronous electric motors by electrical parameters. It is shown that asynchronous electric motors powered from a self-commutated voltage inverter have contained higher harmonic components in addition to the main harmonic. The non-sinusoidal voltage leads to the emerging of the highest current components in the stator winding of the motor. This is the reason for occurring of a pulsating component of the torque on the motor shaft. Therefore, there are two types of ripple: the one caused by the power supply from the self-commutated inverter and the one caused by defects. The moments’ coincidence of these ripples leads to increasing in the amplitude of oscillations. However, significant noise due to the presence of an autonomous inverter does not allow using the current spectrum to diagnose damage. Analysis of the hodographs of the Park’s vector of the stator current and voltage allows one to exclude harmonic components that were formed by the carrier frequency (and multiple of it). At the same time, analyzing the modulus of the Park’s vector and its spectrum, one can note pulsations of the amplitude values of the vector modulus corresponding to certain damage.