Open AccessIMPROVING THE EFFICIENCY OF THE AUTOMATED SYSTEM OF CONTROL FOR OIL TRANSPORTATION PROCESS ON THE BASIS OF INTELLECTUAL TECHNOLOGIES
Author(s) -
O. V. Kuchmistenko
Publication year - 2020
Publication title -
metodi ta priladi kontrolû âkostì
Language(s) - English
Resource type - Journals
eISSN - 2415-3575
pISSN - 1993-9981
DOI - 10.31471/1993-9981-2020-2(45)-58-65
Subject(s) - automation , computer science , pipeline transport , process (computing) , cloud computing , task (project management) , systems engineering , risk analysis (engineering) , industrial engineering , engineering management , engineering , mechanical engineering , medicine , environmental engineering , operating system
The paper considers an urgent scientific and practical task, which consists in the development of new ones. An urgent scientific and practical task is investigated, which consists in the development of new methods and methods for assessing the technical condition of oil trunk pipelines, which will provide safe automated control of the oil transportation system. It has been determined that in conditions of intensive aging of fixed assets of oil transportation systems and financial constraints, complex technical diagnostics of oil trunk pipelines becomes the most effective means of ensuring the reliability and safety of the entire oil transportation system.
Simulation modeling is inherently complex and time-consuming process that requires many computations, including distributed ones. There are several stages of simulation modeling (MI). In the most general, enlarged form, these are the following stages: setting the problem, collecting and processing data, developing and adjusting the model, modeling, accumulating results, planning experiments, analyzing the results, documenting and storing the results. To carry out such research, various systems for the automation of imitation research (SAIS) are being created. A cloud-based approach to conducting MI, which makes it possible to simplify and unify research for the end user, to abstract the researcher from the technical features of the organization of calculations. Cloud AISI is invariant with respect to the target hardware and software. That is why the development of new and promising control and management tools based on artificial intelligence with a combination of cloud technologies is an urgent scientific and practical task, based on the results of which the main scientific problems requiring further research have been identified.