Research and Application of Rod Pump Working Condition Diagnosis and Virtual Production Metering Based on Electric Parameters

The conventional configurations of pumping well IOT consist of electric parameter indicator and dynamometer. The current, voltage, power, and other electrical parameters are easy to access, low costs, stable, and acquired daily during pumping well operation. If the working condition diagnosis and virtual production metering of pumping well can be realized through electrical parameters, the utilization of dynamometers can be cancelled or reduced, which is of great significance to reduce the investment and improve the coverage of IOT in oil wells. The conventional methods of diagnosis and analysis based on electrical parameters and virtual production metering are lack of theoretical basis. The combination of deep learning technology of big data and traditional methods will provide solutions to solve related technical problems. Considering that there are many energy transmission segments from the motor to the downhole pump, the characteristics of the electric parameter curve are more sophisticated and difficult to identify compared with dynamometer card due to the influence of the unbalance, pump fullness, rod/tube vibration, wax deposition and leakage. The shape characteristics of the electric parameter curve of the pumping well are analyzed in the time domain and frequency domain, which provides the basis for further diagnosis, analysis and production measurement. In this paper, an integrated multi-model diagnosis method is proposed. For the working conditions with a large scale of samples, the electrical parameters are converted to dynamometer cards for diagnosis by using the deep learning technology of big data. For the working conditions with sparse samples, the machine learning model is used to diagnosis directly with electrical parameters. The deep learning electric parameter model for production measurement is established. Through the combination of the big data model of electric parameters to dynamometer card, 3D mechanical model of rod string, and big data model of plunger leakage coefficient, the virtual production metering function of pumping well based on electrical parameters is successfully realized. The diagnosis and virtual production metering method and software based on electrical parameters have been applied in many oilfields of CNPC. The accuracy of identifying the upper and lower dead points of electric parameters is 98.0%; the coincidence rate of working condition diagnosis under electrical parameters is 92.0%; the average error of virtual production metering with electric parameters is 13.4%. The dynamometer and gauging room have been canceled in the demonstration area. The application of electrical parameters to diagnose working conditions and meter the production of pumping wells is the key to the low-cost IOT construction. Traditional mathematical and physical methods are difficult to solve this problem, but the application of big data analysis technology could do the job successfully.

Visualization of Control Processes a nd Code Validation

The article contains an overview of articles related to the description of control process visualization. It provides short information on how to visualize the production line based on two programming environments: Factory IO and Inventor together with Matlab/Simulink. The analysis of these two environments concerns control of a virtual 3D object from a real PLC. Both virtual production line projects are based on control from the S7-1214 DC/DC/DC controller. Currently, there is a need to validate the program code or control process which has been done using several commercially available programs.

Research of methods of simulation computer modeling and visualization of complex technological processes at the Department of Engineering Graphics and Design of NRU MIET

The article provides an overview of the topics of bachelor’s and master’s design studies of the Department of Engineering Graphics and Design of NIU MIET. The research results are analyzed. Based on the analysis, recommendations are given regarding the implementation of virtual production spaces and technological equipment, the choice of interactive visualization technology, the development of an effective workflow from a three-dimensional model to an interactive module as part of a VR application, the development of layouts and interface templates.

Digital Transformation of Technological Support of Production in Small Enterprises

Technological transformation involves the integration of medium and small machine-building enterprises into a single field of virtual factories. The integration is based on the strategy of transition to digital production within the framework of national projects and the National Technology Initiative. Divergent thinking is regarded as a driving factor in production and management, which significantly affects all aspects of socio-economic activity. The convergent application of CAD / CAM / CAPP / CAE / CAO ideologies is at the initial stage of use, while individual process components are widely used at all levels of enterprises. The paper considers the development of a group of competencies that ensure the combination of advanced production technologies, as well as their distribution in the field of small and medium-sized machine-building enterprises. The production for markets of new qualities and the development of high-tech directions in the industry lead to the production of globally competitive products. To respond to these trends, deep automation, digitalization, and intellectualization of production processes are required, which implies the combination of material and digital virtual production. A dynamic environment and the challenges it entails need quick and effective decisions to remain competitive in the long term and the ability to accelerate adaptation processes. These total changes are accompanied by the development of fundamentally new business processes at all levels.

SIMULATION OF VIRTUAL DISTRIBUTED PRODUCTION LOCATION UNDER CONDITIONS OF LIMITED POSSIBILITIES OF ENTERPRISE DEVELOPMENT

The task to research the enterprises when locating them in the new areas is posed and solved. The relevance of the problem is related to both moral and physical aging of production systems, which leads to the need for their modernization and reengineering. For the development of the enterprise, new areas are required to accommodate modern technological equipment. Due to the diversification of the company's activities and the appearance of new orders, it is advisable to place modern production lines with a high degree of automation in new areas. The requirements for the organization of new industries, taking into account the concept of Industry 4.0, have led to the creation of enterprises in the form of virtual industries focused on the creation of new innovative products. The aim of the work is to develop models for the rational location of virtual production in the new areas in conditions of limited enterprise capabilities. Due to the complexity of the problem being solved, the study is carried out in three stages: optimization of location on the earth's surface; creation of the communication infrastructure for virtual production; simulation of the virtual enterprise production cycle. The efficient location of virtual production is carried out using both local and multicriteria optimization. In order to create the communication infrastructure of the virtual enterprise the selection of the optimal route for highway laying is carried out. Simulation of the production cycle is carried out considering time delays and queues when performing technological operations. The new scientific result is the solution of the problem of virtual production system locating on the earth's surface, taking into account the proposed indicators and restrictions, which include the cost of land plots renting (acquiring), as well as the costs associated with earth and construction works. Mathematical methods were used: integer optimization, simulation modeling, agent-based modeling. Keywords: virtual enterprise, optimization of technological objects location, communication infrastructure of the enterprise, simulation modeling, agent-based modeling.