Abstract
The paper touches upon the problems of transition to advanced digital, intelligent man-ufacturing technologies, robotic systems, new materials and design methods, the creation of systems for processing large amounts of data, machine learning and artificial intelligence. Automation of fishing process requires an interdisciplinary approach using modern information technologies. The possibility of using artificial intelligence technologies for solving the problems of predictive modeling of the behavior of a trawl system while fishing on a self-learning neural network has been proved. The equations of electric and mechanical drives of trawl winches for controlling the shape-changing design of a midwater trawl are given. The question of improving the control characteristics of a midwater trawl system by introducing a control architecture adapted for the trawl system taking into account the industrial requirements and by developing a mathematical model of the trawl system, in-cluding an accurate model of hydrodynamic forces on the trawl flaps is considered.
Highlights
The paper touches upon the problems of transition to advanced digital, intelligent manufacturing technologies, robotic systems, new materials and design methods, the creation of systems for processing large amounts of data, machine learning and artificial intelligence
The question of improving the control characteristics of a midwater trawl system by introducing a control architecture adapted for the trawl system taking into account the industrial requirements and by developing a mathematical model of the trawl system, including an accurate model of hydrodynamic forces on the trawl flaps is considered
Computer-aided simulation of shape and strength of trawls after changes in design and operational condition // Contributions on the theory of fishing gears and related marine systems
Summary
Калининградский государственный технический университет, Калининград, Российская Федерация. Приведены уравнения электрического и механического приводов траловых лебедок для управления формоизменяемой конструкцией разноглубинного трала. Для решения этой задачи необходимо рассмотреть вопрос о том, как можно улучшить характеристики системы управления траловой лебедкой с учетом промышленных требований к энергосистеме судна, внешних факторов и концепции управления; разработать математическую. Ψ – угол поворота вала; t – время процесса моделирования; D – диаметр барабана; nс – количество намотанных на барабан слоев ваера; hс – шаг слоя намотки; S1 – натяжение в ваере в точке касания барабана; J1 – момент (приведенный) инерции механизма лебедки с ваером, тралом и уловом; i – передаточное отношение редуктора лебедки; C – коэффициент электродвижущей силы и момента ДПТ НВ, имеющий размерность потока магнитной индукции [Нм/А] = [Вс]; I – ток якорной цепи; v – линейная скорость выборки трала; L1 – длина невыбранной части ваера; L0 – общая длина ваера.
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