Збірники наукових праць ЦНТУ
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Item Моніторинг та аналіз нафтових забруднень водних ресурсів з використанням інтелектуальної системи підтримки прийняття рішень(ЦНТУ, 2020) Голик, О. П.; Березюк, І. А.; Мірошніченко, М. С.; Ісмаіл Мухаммед; Holyk, O.; Bereziuk, I.; Miroshnichenko, M.; Mohammad Ismail; Голик, Е. П.; Березюк, И. А.; Мирошниченко, М. С.; Исмаил МухаммедВ статті для аналізу та моніторингу нафтових забруднень водних ресурсів запропоновано розробити інтелектуальну систему підтримки прийняття рішень, яка має в своєму складі базу даних параметрів нафтових забруднень та базу знань способів очистки. Oil production is increasing. This increases the number of accidents. Oil spills are increasing. Since oil has special physical and chemical properties and parameters, contamination of water resources by oil and oil products causes man-made disasters. The authors made the assumption that a robot with artificial intelligence will be used to purify the water surface from oil (oil products) by biological methods. This robot will be located directly on the ship and will monitor and analyze oil pollution. In order to carry out clean-up activities at the site of the accident, it is necessary to have information on the main parameters of oil pollution. The authors of this article propose a structure for the monitoring and analysis of oil pollution in water resources. According to this structure, analysis and monitoring must be carried out by an intelligent decision support system. An intelligent decision support system includes a database of oil pollution parameters and a knowledge base. The aim of this work is to analyze oil pollution on the water surface using an intelligent decision support system. In order to achieve this objective, the article proposes the structure of the oil pollution parameter database, which is part of an intelligent system to support decision-making on oil pollution analysis and assessment. This scheme includes the main parameters of oil pollution affecting the decision on the choice of type and quantity of treatment products for the biological treatment method. An algorithm for determining the capacity of oil spill is proposed. The main elements of the oil pollution parameters database are: type of oil products, capacity of oil spill, water flow, wave height and velocity, wind direction and speed. In future, the analysis and monitoring scheme for oil-based water pollution will be expanded to include special technical, measuring and meteorological instruments that will allow the immediate presence of the oil (oil products) spill investigate oil contamination parameters. В статье для анализа и мониторинга нефтяных загрязнений водных ресурсов предложено разработать интеллектуальную систему поддержки принятия решений, которая включает в себя базу данных параметров нефтяных загрязнений и базу знаний способов очистки.Item Динамічне проектування оптимальної системи стохастичної стабілізації потужності різання для стрічкопилкового верстата(ЦНТУ, 2020) Березюк, І. А.; Голик, О. П.; Солдатенко, В. П.; Bereziuk, I.; Holyk, O.; Soldatenko, V.; Березюк, И. А.; Голик, Е. П.Запропоновано методологічні основи створення оптимальної системи стохастичної стабілізації потужності різання для стрічкопилкового верстата на основі динамічного проектування. Використання новітніх методів структурної ідентифікації для визначення моделей динаміки «системи деревообробний верстат – процес різання» та діючого збурення, методів оптимального синтезу дозволяють забезпечити максимальну якість керування обробкою деревини на зазначеному верстаті при мінімальних затратах та заданих характеристиках оброблюваної поверхні. The article is devoted to the development of methodological foundations for constructing an optimal system of stochastic stabilization of cutting power based on the results of structural identification of models of the dynamics of the system ''woodworking machine-cutting process'' and uncontrolled disturbance. In order to solve the problem of structural identification of the ''woodworking machine-cutting process" system and the disturbance acting in the process of wood-cutting, the article proposes a special technology, the use of which made it possible to determine the transfer function of the ''woodworking machine-cutting process'' and estimate the spectral density of the disturbance acting during the processing. It has been established that when the physical and mechanical properties of wood and the state of the cutting tool change, the structure of the transfer function and spectral density does not change, but only the parameters change. As a result of solving the synthesis problem, the structure and parameters of the optimal controller are determined, which ensures the specified quality of the processed surface with minimal energy consumption. To assess the quality of control, it is proposed to use a quadratic criterion, which is the sum of two weighted variances of the stator current deviation of the main motion motor (characterizes energy costs) and the variance of the feed drive speed control signal.Studies of the robust stability of the optimal system with the obtained controller under the influence of unstructured disturbances made it possible to determine the class and estimate the maximum norms of unstructured disturbances at which the system maintains stability and a given control quality. The use of the proposed approach to the construction of an optimal system of stochastic stabilization of cutting power makes it possible to achieve a reduction in energy costs by 12% for a given quality of the processed surface by increasing the stabilization accuracy by two orders of magnitude. Предложены методологические основы построения оптимальной системы стохастической стабилизации мощности резания для ленточнопильного станка на основе динамического проетирования Использование новых методов структурной идентификации для определения моделей динамики системы «деревообрабатывающий станок-процесс резания» и действующего возмущения, методов оптимального синтеза позволяют обеспечить максимальное качество управления обработкой древесины на данном станке при минимальных затратах и заданных характеристиках обрабатываемой поверхности.Item Структура моніторингу та ідентифікації нафтових забруднень(ЦНТУ, 2019) Голик, О. П.; Волков, І. В.; Ісмаіл Мухаммед; Голик, Е. П.; Волков, И. В; Исмаил Мухаммед; Holyk, O.; Volkov, I.; Mohammad IsmailВ статті запропоновано схему структури загального аналізу нафтових забруднень у режимі реального часу. В даному випадку пропонується для очистки вод від нафтових забруднень використовувати біологічні способи очистки. В статье предложена схема структуры общего анализа нефтяных загрязнений в режиме реального времени. В данном случае предложено для очистки воды от нефтяных загрязнений использовать биологические методы очистки. In different countries, scientists pay attention the method of monitoring, identification and water purification from oil pollutions. The problem of oil pollution is not only relevant for oil producing countries. Oil spills can occur anywhere in the world. The authors of this article propose to develop the robot with artificial intelligence that would monitor, identify and purify water resources from oil pollution in the mode of real time. Previous studies have shown that it is advisable to use biological methods to water purification from oil pollution. To date, scientists have already developed preparations containing a consortium of microorganisms to purify water resources from oil and petroleum products. Microorganisms are able to adapt to large doses of oil. As a result of the biological treatment of petroleum contamination, such microorganisms in the environment remain bacterial protein (which does not require further disposal) and non-toxic oil decay products. The products of the activity of bacteria and the bacteria themselves are easily absorbed by the native microflora, giving the basis for the formation of humus or forming bottom silt. The purpose of this work is to investigate installations for the biological treatment of water resources from oil and petroleum products. In order to achieve this goal, the structure of the scheme of general analysis of oil pollution is proposed in the article. This scheme contains blocks of comparison, determination of the type and amount of contamination. The results are processed using statistical and mathematical analysis methods. The following algorithm is proposed. The robot has a special container for collecting water samples. This container has special sensors that determine the condition of the sample and transmit information to the comparison unit. The comparison unit, based on the knowledge base, determines the conformity of the water sample to the standards. If the amount of pollutants is exceeded, the information goes to the units for determining the amount and type of pollutants. In the results processing unit, decisions are made regarding the method of purification and the amount of purification preparation. In the future, this scheme will be modified and synthesized. More attention should be paid to developing a database and knowledge that is part of an intelligent decision support system. The application of this scheme to the analysis of oil pollution is possible not only for the determination of oil pollution in water resources.Item Обґрунтування автоматизації комп’ютерно-інтегрованої технології ідентифікації та моніторингу нафтових забруднень(ЦНТУ, 2019) Голик, О. П.; Жесан, Р. В.; Ісмаіл, М.; Голик, Е. П.; Жесан, Р. В.; Исмаил, М.; Holyk, O.; Zhesan, R.; Ismail, M.В статті виконано аналіз останніх досліджень з технологій очистки морських вод від нафтових забруднень та обґрунтовано доцільність розробки робота зі штучним інтелектом, який зможе безпосередньо у місці забруднення здійснювати аналіз ступеня забруднення та виконувати відповідні очисні заходи. Запропоновано методику досліджень. В статье выполнен анализ последних исследований технологий очистки морских вод от нефтяных загрязнений и обосновано целесообразность разработки робота с искусственным интеллектом, который сможет непосредственно в месте загрязнения осуществлять анализ степени загрязнения и выполнять соответствующие очистительные действия. Предложена методика исследований. Large oil spills in seawater are not regular, but the damage to the marine ecosystem is significant. Petroleum companies and oil shipment vessels can not prevent oil spills in the future, but they must be prepared to respond quickly to damages. Such technologies are at an early stage of development. The purpose of the article is to study modern automated technologies for monitoring, identification and purification of marine waters from oil pollution. The analysis of recent research has been performed and the need to develop a robot with artificial intelligence has been substantiated. A research methodology and stages of work are proposed. This robot should directly at place oil spill analyze the degree of pollution and clean the sea water. To develop a robot, it is suggested to use statistical methods (for processing data and identifying interactions); mathematical apparatus of fuzzy logic and neural networks; intelligent decision support systems; methods of simulation. Using the database and knowledge base, the robot will be able, depending on the type of pollution, to choose a method of cleaning sea water from oil pollution. In order to develop a robot that should perform the functions of monitoring, identifying and purifying seawater from oil pollution in real time, it is necessary to have information on types of oil spills, their chemical composition and methods of purification. On the basis of the information obtained, create databases and knowledge that will enable the development of the intellectual system with the neural network. Since the impacts of oil pollution can grow rapidly, it is necessary that such works be located directly at the facility (near wells, oil refineries, oil pipelines, etc.), in particular, by sea transport. This can solve the problem of remote sensing of oil spills. In addition, when developing a robot, it is necessary to consider the possibility of analyzing meteorological information. Now is working is ongoing on the accumulation of oil pollution statistics.